Motion vector candidate construction for geometric partitioning mode in video coding

ABSTRACT

A video coder may be configured to determine a partitioning for a block of video data using geometric partitioning mode; construct two uni-prediction motion vector candidate lists for the block of video data, and code the block of video data using uni-prediction based on at least one of the two uni-prediction motion vector candidate lists to generate a decoded block of video data.

This application claims the benefit of U.S. Provisional PatentApplication No. 63/210,883, filed Jun. 15, 2021, the entire content ofwhich is incorporated by reference herein.

TECHNICAL FIELD

This disclosure relates to video encoding and video decoding.

BACKGROUND

Digital video capabilities can be incorporated into a wide range ofdevices, including digital televisions, digital direct broadcastsystems, wireless broadcast systems, personal digital assistants (PDAs),laptop or desktop computers, tablet computers, e-book readers, digitalcameras, digital recording devices, digital media players, video gamingdevices, video game consoles, cellular or satellite radio telephones,so-called “smart phones,” video teleconferencing devices, videostreaming devices, and the like. Digital video devices implement videocoding techniques, such as those described in the standards defined byMPEG-2, MPEG-4, ITU-T H.263, ITU-T H.264/MPEG-4, Part 10, Advanced VideoCoding (AVC), ITU-T H.265/High Efficiency Video Coding (HEVC), ITU-TH.266/Versatile Video Coding (VVC), and extensions of such standards, aswell as proprietary video codecs/formats such as AOMedia Video 1 (AV1)that was developed by the Alliance for Open Media. The video devices maytransmit, receive, encode, decode, and/or store digital videoinformation more efficiently by implementing such video codingtechniques.

Video coding techniques include spatial (intra-picture) predictionand/or temporal (inter-picture) prediction to reduce or removeredundancy inherent in video sequences. For block-based video coding, avideo slice (e.g., a video picture or a portion of a video picture) maybe partitioned into video blocks, which may also be referred to ascoding tree units (CTUs), coding units (CUs) and/or coding nodes. Videoblocks in an intra-coded (I) slice of a picture are encoded usingspatial prediction with respect to reference samples in neighboringblocks in the same picture. Video blocks in an inter-coded (P or B)slice of a picture may use spatial prediction with respect to referencesamples in neighboring blocks in the same picture or temporal predictionwith respect to reference samples in other reference pictures. Picturesmay be referred to as frames, and reference pictures may be referred toas reference frames.

SUMMARY

In general, this disclosure describes techniques for encoding anddecoding video data. In particular, this disclosure describes techniquesfor inter-prediction of blocks of video data partitioned according to ageometric partitioning mode. The techniques of this disclosure includetechniques for merge candidate list construction for geometricpartitioning mode, pruning of merge candidate lists for geometricpartitioning mode, and/or the use of zero motion vectors in geometricpartitioning mode. The techniques of this disclosure may improve thecoding performance of video codecs configured to use a geometricpartitioning mode, including increasing compression and/or reducingdistortion in coded video data.

In one example, a method includes determining a partitioning for a blockof video data using geometric partitioning mode, constructing twouni-prediction motion vector candidate lists for the block of videodata, and decoding the block of video data using uni-prediction based onat least one of the two uni-prediction motion vector candidate lists.

In another example, a device includes a memory and one or moreprocessors in communication with the memory, the one or more processorsconfigured to determine a partitioning for a block of video data usinggeometric partitioning mode, construct two uni-prediction motion vectorcandidate lists for the block of video data, and decode the block ofvideo data using uni-prediction based on at least one of the twouni-prediction motion vector candidate lists.

In another example, a device includes a memory and one or moreprocessors in communication with the memory, the one or more processorsconfigured to determine a partitioning for a block of video data usinggeometric partitioning mode, construct two uni-prediction motion vectorcandidate lists for the block of video data, and encode the block ofvideo data using uni-prediction based on at least one of the twouni-prediction motion vector candidate lists.

In another example, a device includes means for determining apartitioning for a block of video data using geometric partitioningmode, means for constructing two uni-prediction motion vector candidatelists for the block of video data, and means for decoding the block ofvideo data using uni-prediction based on at least one of the twouni-prediction motion vector candidate lists.

In another example, a computer-readable storage medium is encoded withinstructions that, when executed, cause a programmable processor todetermine a partitioning for a block of video data using geometricpartitioning mode, construct two uni-prediction motion vector candidatelists for the block of video data, and decode the block of video datausing uni-prediction based on at least one of the two uni-predictionmotion vector candidate lists.

The details of one or more examples are set forth in the accompanyingdrawings and the description below. Other features, objects, andadvantages will be apparent from the description, drawings, and claims.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 is a block diagram illustrating an example video encoding anddecoding system that may perform the techniques of this disclosure.

FIG. 2 is a conceptual diagram illustrating example geometricpartitions.

FIG. 3 is a table illustrating example merge indices and motion vectorcandidate lists for geometric partition mode.

FIG. 4 is a block diagram illustrating an example video encoder that mayperform the techniques of this disclosure.

FIG. 5 is a block diagram illustrating an example video decoder that mayperform the techniques of this disclosure.

FIG. 6 is a flowchart illustrating an example method for encoding acurrent block in accordance with the techniques of this disclosure.

FIG. 7 is a flowchart illustrating an example method for decoding acurrent block in accordance with the techniques of this disclosure.

FIG. 8 is a flowchart illustrating another example method for encoding acurrent block in accordance with the techniques of this disclosure.

FIG. 9 is a flowchart illustrating another example method for decoding acurrent block in accordance with the techniques of this disclosure.

DETAILED DESCRIPTION

In general, this disclosure describes techniques for encoding anddecoding video data. In particular, this disclosure describes techniquesfor inter-prediction of blocks of video data partitioned according to ageometric partitioning mode. The techniques of this disclosure includetechniques for merge candidate list construction for geometricpartitioning mode, pruning of merge candidate lists for geometricpartitioning mode, and/or the use of zero motion vectors in geometricpartitioning mode. The techniques of this disclosure may improve thecoding performance of video codecs configured to use a geometricpartitioning mode, including increasing compression and/or reducingdistortion in coded video data.

FIG. 1 is a block diagram illustrating an example video encoding anddecoding system 100 that may perform the techniques of this disclosure.The techniques of this disclosure are generally directed to coding(encoding and/or decoding) video data. In general, video data includesany data for processing a video. Thus, video data may include raw,unencoded video, encoded video, decoded (e.g., reconstructed) video, andvideo metadata, such as signaling data.

As shown in FIG. 1 , system 100 includes a source device 102 thatprovides encoded video data to be decoded and displayed by a destinationdevice 116, in this example. In particular, source device 102 providesthe video data to destination device 116 via a computer-readable medium110. Source device 102 and destination device 116 may comprise any of awide range of devices, including desktop computers, notebook (i.e.,laptop) computers, mobile devices, tablet computers, set-top boxes,telephone handsets such as smartphones, televisions, cameras, displaydevices, digital media players, video gaming consoles, video streamingdevice, broadcast receiver devices, or the like. In some cases, sourcedevice 102 and destination device 116 may be equipped for wirelesscommunication, and thus may be referred to as wireless communicationdevices.

In the example of FIG. 1 , source device 102 includes video source 104,memory 106, video encoder 200, and output interface 108. Destinationdevice 116 includes input interface 122, video decoder 300, memory 120,and display device 118. In accordance with this disclosure, videoencoder 200 of source device 102 and video decoder 300 of destinationdevice 116 may be configured to apply the techniques for merge candidatelist construction for geometric partitioning mode. Thus, source device102 represents an example of a video encoding device, while destinationdevice 116 represents an example of a video decoding device. In otherexamples, a source device and a destination device may include othercomponents or arrangements. For example, source device 102 may receivevideo data from an external video source, such as an external camera.Likewise, destination device 116 may interface with an external displaydevice, rather than include an integrated display device.

System 100 as shown in FIG. 1 is merely one example. In general, anydigital video encoding and/or decoding device may perform techniques formerge candidate list construction for geometric partitioning mode.Source device 102 and destination device 116 are merely examples of suchcoding devices in which source device 102 generates coded video data fortransmission to destination device 116. This disclosure refers to a“coding” device as a device that performs coding (encoding and/ordecoding) of data. Thus, video encoder 200 and video decoder 300represent examples of coding devices, in particular, a video encoder anda video decoder, respectively. In some examples, source device 102 anddestination device 116 may operate in a substantially symmetrical mannersuch that each of source device 102 and destination device 116 includesvideo encoding and decoding components. Hence, system 100 may supportone-way or two-way video transmission between source device 102 anddestination device 116, e.g., for video streaming, video playback, videobroadcasting, or video telephony.

In general, video source 104 represents a source of video data (i.e.,raw, unencoded video data) and provides a sequential series of pictures(also referred to as “frames”) of the video data to video encoder 200,which encodes data for the pictures. Video source 104 of source device102 may include a video capture device, such as a video camera, a videoarchive containing previously captured raw video, and/or a video feedinterface to receive video from a video content provider. As a furtheralternative, video source 104 may generate computer graphics-based dataas the source video, or a combination of live video, archived video, andcomputer-generated video. In each case, video encoder 200 encodes thecaptured, pre-captured, or computer-generated video data. Video encoder200 may rearrange the pictures from the received order (sometimesreferred to as “display order”) into a coding order for coding. Videoencoder 200 may generate a bitstream including encoded video data.Source device 102 may then output the encoded video data via outputinterface 108 onto computer-readable medium 110 for reception and/orretrieval by, e.g., input interface 122 of destination device 116.

Memory 106 of source device 102 and memory 120 of destination device 116represent general purpose memories. In some examples, memories 106, 120may store raw video data, e.g., raw video from video source 104 and raw,decoded video data from video decoder 300. Additionally oralternatively, memories 106, 120 may store software instructionsexecutable by, e.g., video encoder 200 and video decoder 300,respectively. Although memory 106 and memory 120 are shown separatelyfrom video encoder 200 and video decoder 300 in this example, it shouldbe understood that video encoder 200 and video decoder 300 may alsoinclude internal memories for functionally similar or equivalentpurposes. Furthermore, memories 106, 120 may store encoded video data,e.g., output from video encoder 200 and input to video decoder 300. Insome examples, portions of memories 106, 120 may be allocated as one ormore video buffers, e.g., to store raw, decoded, and/or encoded videodata.

Computer-readable medium 110 may represent any type of medium or devicecapable of transporting the encoded video data from source device 102 todestination device 116. In one example, computer-readable medium 110represents a communication medium to enable source device 102 totransmit encoded video data directly to destination device 116 inreal-time, e.g., via a radio frequency network or computer-basednetwork. Output interface 108 may modulate a transmission signalincluding the encoded video data, and input interface 122 may demodulatethe received transmission signal, according to a communication standard,such as a wireless communication protocol. The communication medium maycomprise any wireless or wired communication medium, such as a radiofrequency (RF) spectrum or one or more physical transmission lines. Thecommunication medium may form part of a packet-based network, such as alocal area network, a wide-area network, or a global network such as theInternet. The communication medium may include routers, switches, basestations, or any other equipment that may be useful to facilitatecommunication from source device 102 to destination device 116.

In some examples, source device 102 may output encoded data from outputinterface 108 to storage device 112. Similarly, destination device 116may access encoded data from storage device 112 via input interface 122.Storage device 112 may include any of a variety of distributed orlocally accessed data storage media such as a hard drive, Blu-ray discs,DVDs, CD-ROMs, flash memory, volatile or non-volatile memory, or anyother suitable digital storage media for storing encoded video data.

In some examples, source device 102 may output encoded video data tofile server 114 or another intermediate storage device that may storethe encoded video data generated by source device 102. Destinationdevice 116 may access stored video data from file server 114 viastreaming or download.

File server 114 may be any type of server device capable of storingencoded video data and transmitting that encoded video data to thedestination device 116. File server 114 may represent a web server(e.g., for a website), a server configured to provide a file transferprotocol service (such as File Transfer Protocol (FTP) or File Deliveryover Unidirectional Transport (FLUTE) protocol), a content deliverynetwork (CDN) device, a hypertext transfer protocol (HTTP) server, aMultimedia Broadcast Multicast Service (MBMS) or Enhanced MBMS (eMBMS)server, and/or a network attached storage (NAS) device. File server 114may, additionally or alternatively, implement one or more HTTP streamingprotocols, such as Dynamic Adaptive Streaming over HTTP (DASH), HTTPLive Streaming (HLS), Real Time Streaming Protocol (RTSP), HTTP DynamicStreaming, or the like.

Destination device 116 may access encoded video data from file server114 through any standard data connection, including an Internetconnection. This may include a wireless channel (e.g., a Wi-Ficonnection), a wired connection (e.g., digital subscriber line (DSL),cable modem, etc.), or a combination of both that is suitable foraccessing encoded video data stored on file server 114. Input interface122 may be configured to operate according to any one or more of thevarious protocols discussed above for retrieving or receiving media datafrom file server 114, or other such protocols for retrieving media data.

Output interface 108 and input interface 122 may represent wirelesstransmitters/receivers, modems, wired networking components (e.g.,Ethernet cards), wireless communication components that operateaccording to any of a variety of IEEE 802.11 standards, or otherphysical components. In examples where output interface 108 and inputinterface 122 comprise wireless components, output interface 108 andinput interface 122 may be configured to transfer data, such as encodedvideo data, according to a cellular communication standard, such as 4G,4G-LTE (Long-Term Evolution), LTE Advanced, 5G, or the like. In someexamples where output interface 108 comprises a wireless transmitter,output interface 108 and input interface 122 may be configured totransfer data, such as encoded video data, according to other wirelessstandards, such as an IEEE 802.11 specification, an IEEE 802.15specification (e.g., ZigBee™), a Bluetooth™ standard, or the like. Insome examples, source device 102 and/or destination device 116 mayinclude respective system-on-a-chip (SoC) devices. For example, sourcedevice 102 may include an SoC device to perform the functionalityattributed to video encoder 200 and/or output interface 108, anddestination device 116 may include an SoC device to perform thefunctionality attributed to video decoder 300 and/or input interface122.

The techniques of this disclosure may be applied to video coding insupport of any of a variety of multimedia applications, such asover-the-air television broadcasts, cable television transmissions,satellite television transmissions, Internet streaming videotransmissions, such as dynamic adaptive streaming over HTTP (DASH),digital video that is encoded onto a data storage medium, decoding ofdigital video stored on a data storage medium, or other applications.

Input interface 122 of destination device 116 receives an encoded videobitstream from computer-readable medium 110 (e.g., a communicationmedium, storage device 112, file server 114, or the like). The encodedvideo bitstream may include signaling information defined by videoencoder 200, which is also used by video decoder 300, such as syntaxelements having values that describe characteristics and/or processingof video blocks or other coded units (e.g., slices, pictures, groups ofpictures, sequences, or the like). Display device 118 displays decodedpictures of the decoded video data to a user. Display device 118 mayrepresent any of a variety of display devices such as a liquid crystaldisplay (LCD), a plasma display, an organic light emitting diode (OLED)display, or another type of display device.

Although not shown in FIG. 1 , in some examples, video encoder 200 andvideo decoder 300 may each be integrated with an audio encoder and/oraudio decoder, and may include appropriate MUX-DEMUX units, or otherhardware and/or software, to handle multiplexed streams including bothaudio and video in a common data stream.

Video encoder 200 and video decoder 300 each may be implemented as anyof a variety of suitable encoder and/or decoder circuitry, such as oneor more microprocessors, digital signal processors (DSPs), applicationspecific integrated circuits (ASICs), field programmable gate arrays(FPGAs), discrete logic, software, hardware, firmware or anycombinations thereof. When the techniques are implemented partially insoftware, a device may store instructions for the software in asuitable, non-transitory computer-readable medium and execute theinstructions in hardware using one or more processors to perform thetechniques of this disclosure. Each of video encoder 200 and videodecoder 300 may be included in one or more encoders or decoders, eitherof which may be integrated as part of a combined encoder/decoder (CODEC)in a respective device. A device including video encoder 200 and/orvideo decoder 300 may comprise an integrated circuit, a microprocessor,and/or a wireless communication device, such as a cellular telephone.

Video encoder 200 and video decoder 300 may operate according to a videocoding standard, such as ITU-T H.265, also referred to as HighEfficiency Video Coding (HEVC) or extensions thereto, such as themulti-view and/or scalable video coding extensions. Alternatively, videoencoder 200 and video decoder 300 may operate according to otherproprietary or industry standards, such as ITU-T H.266, also referred toas Versatile Video Coding (VVC). In other examples, video encoder 200and video decoder 300 may operate according to a proprietary videocodec/format, such as AOMedia Video 1 (AV1), extensions of AV1, and/orsuccessor versions of AV1 (e.g., AV2). In other examples, video encoder200 and video decoder 300 may operate according to other proprietaryformats or industry standards. The techniques of this disclosure,however, are not limited to any particular coding standard or format. Ingeneral, video encoder 200 and video decoder 300 may be configured toperform the techniques of this disclosure in conjunction with any videocoding techniques that use a geometric partitioning mode.

In general, video encoder 200 and video decoder 300 may performblock-based coding of pictures. The term “block” generally refers to astructure including data to be processed (e.g., encoded, decoded, orotherwise used in the encoding and/or decoding process). For example, ablock may include a two-dimensional matrix of samples of luminanceand/or chrominance data. In general, video encoder 200 and video decoder300 may code video data represented in a YUV (e.g., Y, Cb, Cr) format.That is, rather than coding red, green, and blue (RGB) data for samplesof a picture, video encoder 200 and video decoder 300 may code luminanceand chrominance components, where the chrominance components may includeboth red hue and blue hue chrominance components. In some examples,video encoder 200 converts received RGB formatted data to a YUVrepresentation prior to encoding, and video decoder 300 converts the YUVrepresentation to the RGB format. Alternatively, pre- andpost-processing units (not shown) may perform these conversions.

This disclosure may generally refer to coding (e.g., encoding anddecoding) of pictures to include the process of encoding or decodingdata of the picture. Similarly, this disclosure may refer to coding ofblocks of a picture to include the process of encoding or decoding datafor the blocks, e.g., prediction and/or residual coding. An encodedvideo bitstream generally includes a series of values for syntaxelements representative of coding decisions (e.g., coding modes) andpartitioning of pictures into blocks. Thus, references to coding apicture or a block should generally be understood as coding values forsyntax elements forming the picture or block.

HEVC defines various blocks, including coding units (CUs), predictionunits (PUs), and transform units (TUs). According to HEVC, a video coder(such as video encoder 200) partitions a coding tree unit (CTU) into CUsaccording to a quadtree structure. That is, the video coder partitionsCTUs and CUs into four equal, non-overlapping squares, and each node ofthe quadtree has either zero or four child nodes. Nodes without childnodes may be referred to as “leaf nodes,” and CUs of such leaf nodes mayinclude one or more PUs and/or one or more TUs. The video coder mayfurther partition PUs and TUs. For example, in HEVC, a residual quadtree(RQT) represents partitioning of TUs. In HEVC, PUs representinter-prediction data, while TUs represent residual data. CUs that areintra-predicted include intra-prediction information, such as anintra-mode indication.

As another example, video encoder 200 and video decoder 300 may beconfigured to operate according to VVC. According to VVC, a video coder(such as video encoder 200) partitions a picture into a plurality ofcoding tree units (CTUs). Video encoder 200 may partition a CTUaccording to a tree structure, such as a quadtree-binary tree (QTBT)structure or Multi-Type Tree (MTT) structure. The QTBT structure removesthe concepts of multiple partition types, such as the separation betweenCUs, PUs, and TUs of HEVC. A QTBT structure includes two levels: a firstlevel partitioned according to quadtree partitioning, and a second levelpartitioned according to binary tree partitioning. A root node of theQTBT structure corresponds to a CTU. Leaf nodes of the binary treescorrespond to coding units (CUs).

In an MTT partitioning structure, blocks may be partitioned using aquadtree (QT) partition, a binary tree (BT) partition, and one or moretypes of triple tree (TT) (also called ternary tree (TT)) partitions. Atriple or ternary tree partition is a partition where a block is splitinto three sub-blocks. In some examples, a triple or ternary treepartition divides a block into three sub-blocks without dividing theoriginal block through the center. The partitioning types in MTT (e.g.,QT, BT, and TT), may be symmetrical or asymmetrical.

When operating according to the AV1 codec, video encoder 200 and videodecoder 300 may be configured to code video data in blocks. In AV1, thelargest coding block that can be processed is called a superblock. InAV1, a superblock can be either 128×128 luma samples or 64×64 lumasamples. However, in successor video coding formats (e.g., AV2), asuperblock may be defined by different (e.g., larger) luma sample sizes.In some examples, a superblock is the top level of a block quadtree.Video encoder 200 may further partition a superblock into smaller codingblocks. Video encoder 200 may partition a superblock and other codingblocks into smaller blocks using square or non-square partitioning.Non-square blocks may include N/2×N, N×N/2, N/4×N, and N×N/4 blocks.Video encoder 200 and video decoder 300 may perform separate predictionand transform processes on each of the coding blocks.

AV1 also defines a tile of video data. A tile is a rectangular array ofsuperblocks that may be coded independently of other tiles. That is,video encoder 200 and video decoder 300 may encode and decode,respectively, coding blocks within a tile without using video data fromother tiles. However, video encoder 200 and video decoder 300 mayperform filtering across tile boundaries. Tiles may be uniform ornon-uniform in size. Tile-based coding may enable parallel processingand/or multi-threading for encoder and decoder implementations.

In some examples, video encoder 200 and video decoder 300 may use asingle QTBT or MTT structure to represent each of the luminance andchrominance components, while in other examples, video encoder 200 andvideo decoder 300 may use two or more QTBT or MTT structures, such asone QTBT/MTT structure for the luminance component and another QTBT/MTTstructure for both chrominance components (or two QTBT/MTT structuresfor respective chrominance components).

Video encoder 200 and video decoder 300 may be configured to usequadtree partitioning, QTBT partitioning, MTT partitioning, superblockpartitioning, or other partitioning structures.

In some examples, a CTU includes a coding tree block (CTB) of lumasamples, two corresponding CTBs of chroma samples of a picture that hasthree sample arrays, or a CTB of samples of a monochrome picture or apicture that is coded using three separate color planes and syntaxstructures used to code the samples. A CTB may be an N×N block ofsamples for some value of N such that the division of a component intoCTBs is a partitioning. A component is an array or single sample fromone of the three arrays (luma and two chroma) that compose a picture in4:2:0, 4:2:2, or 4:4:4 color format or the array or a single sample ofthe array that compose a picture in monochrome format. In some examples,a coding block is an M×N block of samples for some values of M and Nsuch that a division of a CTB into coding blocks is a partitioning.

The blocks (e.g., CTUs or CUs) may be grouped in various ways in apicture. As one example, a brick may refer to a rectangular region ofCTU rows within a particular tile in a picture. A tile may be arectangular region of CTUs within a particular tile column and aparticular tile row in a picture. A tile column refers to a rectangularregion of CTUs having a height equal to the height of the picture and awidth specified by syntax elements (e.g., such as in a picture parameterset). A tile row refers to a rectangular region of CTUs having a heightspecified by syntax elements (e.g., such as in a picture parameter set)and a width equal to the width of the picture.

In some examples, a tile may be partitioned into multiple bricks, eachof which may include one or more CTU rows within the tile. A tile thatis not partitioned into multiple bricks may also be referred to as abrick. However, a brick that is a true subset of a tile may not bereferred to as a tile. The bricks in a picture may also be arranged in aslice. A slice may be an integer number of bricks of a picture that maybe exclusively contained in a single network abstraction layer (NAL)unit. In some examples, a slice includes either a number of completetiles or only a consecutive sequence of complete bricks of one tile.

This disclosure may use “N×N” and “N by N” interchangeably to refer tothe sample dimensions of a block (such as a CU or other video block) interms of vertical and horizontal dimensions, e.g., 16×16 samples or 16by 16 samples. In general, a 16×16 CU will have 16 samples in a verticaldirection (y=16) and 16 samples in a horizontal direction (x=16).Likewise, an N×N CU generally has N samples in a vertical direction andN samples in a horizontal direction, where N represents a nonnegativeinteger value. The samples in a CU may be arranged in rows and columns.Moreover, CUs need not necessarily have the same number of samples inthe horizontal direction as in the vertical direction. For example, CUsmay comprise N×M samples, where M is not necessarily equal to N.

Video encoder 200 encodes video data for CUs representing predictionand/or residual information, and other information. The predictioninformation indicates how the CU is to be predicted in order to form aprediction block for the CU. The residual information generallyrepresents sample-by-sample differences between samples of the CU priorto encoding and the prediction block.

To predict a CU, video encoder 200 may generally form a prediction blockfor the CU through inter-prediction or intra-prediction.Inter-prediction generally refers to predicting the CU from data of apreviously coded picture, whereas intra-prediction generally refers topredicting the CU from previously coded data of the same picture. Toperform inter-prediction, video encoder 200 may generate the predictionblock using one or more motion vectors. Video encoder 200 may generallyperform a motion search to identify a reference block that closelymatches the CU, e.g., in terms of differences between the CU and thereference block. Video encoder 200 may calculate a difference metricusing a sum of absolute difference (SAD), sum of squared differences(SSD), mean absolute difference (MAD), mean squared differences (MSD),or other such difference calculations to determine whether a referenceblock closely matches the current CU. In some examples, video encoder200 may predict the current CU using uni-directional prediction orbi-directional prediction.

Some examples of VVC also provide an affine motion compensation mode,which may be considered an inter-prediction mode. In affine motioncompensation mode, video encoder 200 may determine two or more motionvectors that represent non-translational motion, such as zoom in or out,rotation, perspective motion, or other irregular motion types.

To perform intra-prediction, video encoder 200 may select anintra-prediction mode to generate the prediction block. Some examples ofVVC provide sixty-seven intra-prediction modes, including variousdirectional modes, as well as planar mode and DC mode. In general, videoencoder 200 selects an intra-prediction mode that describes neighboringsamples to a current block (e.g., a block of a CU) from which to predictsamples of the current block. Such samples may generally be above, aboveand to the left, or to the left of the current block in the same pictureas the current block, assuming video encoder 200 codes CTUs and CUs inraster scan order (left to right, top to bottom).

Video encoder 200 encodes data representing the prediction mode for acurrent block. For example, for inter-prediction modes, video encoder200 may encode data representing which of the various availableinter-prediction modes is used, as well as motion information for thecorresponding mode. For uni-directional or bi-directionalinter-prediction, for example, video encoder 200 may encode motionvectors using advanced motion vector prediction (AMVP) or merge mode.Video encoder 200 may use similar modes to encode motion vectors foraffine motion compensation mode.

AV1 includes two general techniques for encoding and decoding a codingblock of video data. The two general techniques are intra prediction(e.g., intra frame prediction or spatial prediction) and interprediction (e.g., inter frame prediction or temporal prediction). In thecontext of AV1, when predicting blocks of a current frame of video datausing an intra prediction mode, video encoder 200 and video decoder 300do not use video data from other frames of video data. For most intraprediction modes, video encoder 200 encodes blocks of a current framebased on the difference between sample values in the current block andpredicted values generated from reference samples in the same frame.Video encoder 200 determines predicted values generated from thereference samples based on the intra prediction mode.

Following prediction, such as intra-prediction or inter-prediction of ablock, video encoder 200 may calculate residual data for the block. Theresidual data, such as a residual block, represents sample by sampledifferences between the block and a prediction block for the block,formed using the corresponding prediction mode. Video encoder 200 mayapply one or more transforms to the residual block, to producetransformed data in a transform domain instead of the sample domain. Forexample, video encoder 200 may apply a discrete cosine transform (DCT),an integer transform, a wavelet transform, or a conceptually similartransform to residual video data. Additionally, video encoder 200 mayapply a secondary transform following the first transform, such as amode-dependent non-separable secondary transform (MDNSST), a signaldependent transform, a Karhunen-Loeve transform (KLT), or the like.Video encoder 200 produces transform coefficients following applicationof the one or more transforms.

As noted above, following any transforms to produce transformcoefficients, video encoder 200 may perform quantization of thetransform coefficients. Quantization generally refers to a process inwhich transform coefficients are quantized to possibly reduce the amountof data used to represent the transform coefficients, providing furthercompression. By performing the quantization process, video encoder 200may reduce the bit depth associated with some or all of the transformcoefficients. For example, video encoder 200 may round an n-bit valuedown to an m-bit value during quantization, where n is greater than m.In some examples, to perform quantization, video encoder 200 may performa bitwise right-shift of the value to be quantized.

Following quantization, video encoder 200 may scan the transformcoefficients, producing a one-dimensional vector from thetwo-dimensional matrix including the quantized transform coefficients.The scan may be designed to place higher energy (and therefore lowerfrequency) transform coefficients at the front of the vector and toplace lower energy (and therefore higher frequency) transformcoefficients at the back of the vector. In some examples, video encoder200 may utilize a predefined scan order to scan the quantized transformcoefficients to produce a serialized vector, and then entropy encode thequantized transform coefficients of the vector. In other examples, videoencoder 200 may perform an adaptive scan. After scanning the quantizedtransform coefficients to form the one-dimensional vector, video encoder200 may entropy encode the one-dimensional vector, e.g., according tocontext-adaptive binary arithmetic coding (CABAC). Video encoder 200 mayalso entropy encode values for syntax elements describing metadataassociated with the encoded video data for use by video decoder 300 indecoding the video data.

To perform CABAC, video encoder 200 may assign a context within acontext model to a symbol to be transmitted. The context may relate to,for example, whether neighboring values of the symbol are zero-valued ornot. The probability determination may be based on a context assigned tothe symbol.

Video encoder 200 may further generate syntax data, such as block-basedsyntax data, picture-based syntax data, and sequence-based syntax data,to video decoder 300, e.g., in a picture header, a block header, a sliceheader, or other syntax data, such as a sequence parameter set (SPS),picture parameter set (PPS), or video parameter set (VPS). Video decoder300 may likewise decode such syntax data to determine how to decodecorresponding video data.

In this manner, video encoder 200 may generate a bitstream includingencoded video data, e.g., syntax elements describing partitioning of apicture into blocks (e.g., CUs) and prediction and/or residualinformation for the blocks. Ultimately, video decoder 300 may receivethe bitstream and decode the encoded video data.

In general, video decoder 300 performs a reciprocal process to thatperformed by video encoder 200 to decode the encoded video data of thebitstream. For example, video decoder 300 may decode values for syntaxelements of the bitstream using CABAC in a manner substantially similarto, albeit reciprocal to, the CABAC encoding process of video encoder200. The syntax elements may define partitioning information forpartitioning of a picture into CTUs, and partitioning of each CTUaccording to a corresponding partition structure, such as a QTBTstructure, to define CUs of the CTU. The syntax elements may furtherdefine prediction and residual information for blocks (e.g., CUs) ofvideo data.

The residual information may be represented by, for example, quantizedtransform coefficients. Video decoder 300 may inverse quantize andinverse transform the quantized transform coefficients of a block toreproduce a residual block for the block. Video decoder 300 uses asignaled prediction mode (intra- or inter-prediction) and relatedprediction information (e.g., motion information for inter-prediction)to form a prediction block for the block. Video decoder 300 may thencombine the prediction block and the residual block (on asample-by-sample basis) to reproduce the original block. Video decoder300 may perform additional processing, such as performing a deblockingprocess to reduce visual artifacts along boundaries of the block. Thisdisclosure may generally refer to “signaling” certain information, suchas syntax elements. The term “signaling” may generally refer to thecommunication of values for syntax elements and/or other data used todecode encoded video data. That is, video encoder 200 may signal valuesfor syntax elements in the bitstream. In general, signaling refers togenerating a value in the bitstream. As noted above, source device 102may transport the bitstream to destination device 116 substantially inreal time, or not in real time, such as might occur when storing syntaxelements to storage device 112 for later retrieval by destination device116.

The Versatile Video Coding (VVC) standard was developed by Joint VideoExperts Team (JVET) of ITU-T and ISO/IEC to achieve substantialcompression capability beyond the High Efficiency Video Coding (HEVC)standard for a broad range of applications. The VVC specification wasfinalized in July 2020 and published by both ITU-T and ISO/IEC. The VVCspecification specifies normative bitstream and picture formats, highlevel syntax (HLS), coding unit level syntax, and the parsing anddecoding process. VVC also specifies profiles/tiers/levels (PTL)restrictions, byte stream formats, a hypothetical reference decoder, andsupplemental enhancement information (SEI) in the annex. The techniquesof this disclosure, as will be described below, may be applied toextensions of VVC, AV1, or any future video coding standards or formatsthat use a geometric partitioning mode.

This disclosure describes techniques for inter-prediction of blocks ofvideo data partitioned according to a geometric partitioning mode. Thetechniques of this disclosure include techniques of merge candidate listconstruction for geometric partitioning mode, pruning of merge candidatelists for geometric partitioning mode, and/or the use of zero motionvectors in geometric partitioning mode. The techniques of thisdisclosure may improve the coding performance of video codecs configuredto use a geometric partitioning mode, including increasing compressionand/or reducing distortion in coded video data. In accordance with thetechniques of this disclosure, as will be described in more detailbelow, video encoder 200 and/or video decoder 300 may be configured todetermine a partitioning for a block of video data using geometricpartitioning mode, construct two uni-prediction motion vector candidatelists for the block of video data, and code the block of video datausing uni-prediction based on at least one of the two uni-predictionmotion vector candidate lists.

In VVC, a geometric partitioning mode (GPM) is supported for interprediction. Video encoder 200 may signal the use of the geometricpartitioning mode using a CU-level flag. Video encoder 200 and videodecoder 300 code video data using the geometric partitioning mode usinga specific kind of merge mode, with other merge modes including theregular merge mode, the merge with motion vector difference (MMVD) mode,the combined inter-intra prediction (CIIP) mode, and the subblock mergemode. In total, 64 partitions are supported by the geometricpartitioning mode in VVC for each possible CU size w×h=2^(m)×2^(n), withm, n∈{3 . . . 6}, excluding 8×64 and 64×8.

FIG. 2 is a conceptual diagram illustrating example geometricpartitions. When the geometric partitioning mode is used, video encoder200 splits one of CUs 400 into two parts by a geometrically locatedstraight line, as shown in FIG. 2 . Video encoder 200 and video decoder300 mathematically derive the location of the splitting line from anangle and offset parameters of a specific partition. Video encoder 200and video decoder 300 may be configured to code each part of a geometricpartition in the CU using inter-prediction using separate motion vectorsfor each partition. In one example, only uni-prediction is allowed foreach partition. That is, each partition is associated with one motionvector and one reference index. The uni-prediction motion for eachpartition is derived as described below.

When operating according to VVC, video encoder 200 and video decoder 300are configured to derive the uni-prediction candidate list for geometricpartitioning mode directly from the merge candidate list constructed forregular merge mode. Denote n as the index of the uni-prediction motionin the geometric uni-prediction candidate list. The LX motion vector ofthe n-th merge candidate, with X equal to the parity (even or odd) of n,is used as the n-th uni-prediction motion vector for geometricpartitioning mode. In this context, LX reference to the referencepicture list 0 or 1 (e.g., L0 and L1, where X may be 0 or 1). FIG. 3shows a table 410 illustrating example merge indices and motion vectorcandidate lists for geometric partition mode. The motion vectors forgeometric partitioning mode are marked with “x” in FIG. 3 . In case acorresponding LX motion vector of the n-th extended merge candidate doesnot exist, the L(1−X) motion vector of the same candidate is usedinstead as the uni-prediction motion vector for geometric partitioningmode.

If geometric partitioning mode is used for a current CU, then ageometric partition index indicating the partition mode of the geometricpartition (e.g., angle and offset), and two merge indices (one for eachpartition) are further signalled. The number of a maximum geometricpartitioning mode candidate size is signalled explicitly in an SPS andspecifies a syntax binarization for geometric partitioning mode mergeindices. After predicting each of part of the geometric partition, thesample values along the geometric partition edge are adjusted usingblending processing with adaptive weights.

This disclosure describes the following techniques for merge motionvector candidate list construction, pruning, and zero motion vectorpadding for geometric partitioning mode. The techniques of thisdisclosure may improve coding efficiency and/or reduce distortion forpictures of video data coded using geometric partitioning mode. Thetechniques of the disclosure described below may be applied individuallyor in any combination.

GEO MV List Construction

In one example of the disclosure, a geometric partitioning mode (GEO)motion vector (MV) candidate list construction is described. Thisexample is described with relation to GEO MV candidate listconstruction, but the techniques of this example may be useful otherinter prediction modes that only use uni-prediction (e.g., only uses onereference picture list).

In this example, rather than using the merge candidate list from regularmerge mode, video encoder 200 and video decoder 300 may be configured toconstruct two uni-prediction MV candidate lists (e.g., a first candidatelist and a second candidate list) for GEO MV prediction when usinggeometric partitioning mode. Both candidate lists include L0 (list 0) MVcandidates and L1 (list 1) MV candidates. L0 MV candidates are from afirst reference picture list (L0) and L1 MV candidates are from a secondreference picture list (L1). L0 MV candidates may have a higher prioritythan L1 MV candidates in the first candidate list, and L1 MV candidatesmay have a higher priority than L0 MV candidates in the second candidatelist.

In this context, higher priority means that a particular MV candidatefrom a particular reference picture list are added first in aninterleaved fashion. As such, for the first candidate list, MVcandidates from both L0 and L1 are interleaved, with L0 MV candidatesbeing added first. For example, the first candidate list may include MVcandidates in the following order: C-L0, C-L1, C-L0, C-L1 . . . C-L0represents an MV candidate from list L0 and C-L1 represents an MVcandidate from list L1. Accordingly, for the second candidate list, MVcandidates from both L0 and L1 are interleaved, with L1 MV candidatesbeing added first. For example, the first candidate list may include MVcandidates in the following order: C-L1, C-L0, C-L1, C-L0 . . . .

Accordingly, in one example of the disclosure, video encoder 200 andvideo decoder 300 may be configured to determine a partitioning for ablock of video data using geometric partitioning mode, construct twouni-prediction motion vector candidate lists for the block of video dataand code the block of video data using uni-prediction based on at leastone of the two uni-prediction motion vector candidate lists. The twouni-prediction MV candidate lists include a first uni-prediction MVcandidate list (first candidate list) and a second uni-prediction MVcandidate list (second candidate list).

To construct the two uni-prediction motion vector candidate lists forthe block of video data, video encoder 200 and video decoder 300 mayconstruct a first candidate list of the two uni-prediction motion vectorcandidate lists, including interleaving first motion vector candidatesfrom a first reference picture list with second motion vector candidatesfrom a second reference picture list, and may construct a secondcandidate list of the two uni-prediction motion vector candidate lists,including interleaving the second motion vector candidates from thesecond reference picture list with the first motion vector candidatesfrom the first reference picture list.

In this context, interleaving first motion vector candidates from thefirst reference picture list with second motion vector candidates fromthe second reference picture list comprises adding the first motionvector candidates and the second motion vector candidates to the firstcandidate list in an alternating fashion wherein a candidate from thefirst motion vector candidates is added first. Likewise, interleavingsecond motion vector candidates from the second reference picture listwith first motion vector candidates from the first reference picturelist comprises adding the second motion vector candidates and the firstmotion vector candidates to the second candidate list in an alternatingfashion wherein a candidate from the second motion vector candidates isadded first.

In one example, in the first uni-prediction MV candidate list (firstcandidate list), a base MV of the n-th uni-prediction motion vector forthe first uni-prediction MV candidate list may be set equal to the n-thregular merge candidate (e.g., from the regular merge mode candidatelist). The motion vector of the List X of the n-th base MV, with X equalto 0 or 1, is used as the n-th uni-prediction motion vector for thefirst uni-prediction MV candidate list. In case a corresponding LXmotion vector of the n-th base MV does not exist, the L(1−X) motionvector of the same base MV candidate is used.

In another example, the base MV of the n-th uni-prediction motion vectorin the first uni-prediction MV candidate list can be constructed from MVcandidates of neighboring blocks, collocated blocks, or other blockswith a certain checking order, instead of the n-th regular mergecandidate.

In the second uni-prediction MV candidate list (second candidate list),a base MV of the n-th uni-prediction motion vector for the seconduni-prediction MV candidate list may be set equal to the n-th regularmerge candidate. Then the motion vector of List Y of the n-th base MV,with Y equal to 1 or 0, is used as the n-th uni-prediction motion vectorfor the second uni-prediction MV candidate list. In case a correspondingLY motion vector of the n-th base MV does not exist, the L(1−Y) motionvector of the same base MV candidate is used.

In the above examples, the relationship between X and Y is Y=1−X, whereX may have values of 0 and 1.

In another example, the base MV of the n-th uni-prediction motion vectorin the second uni-prediction MV candidate list can be constructed fromMV candidates of neighboring blocks, collocated blocks, or other blockswith a certain checking order, instead of the n-th regular mergecandidate.

Video encoder 200 and video decoder 300 may construct a final GEO MVcandidate list from the first uni-prediction MV candidate list (firstcandidate list), the second uni-prediction MV candidate list (secondcandidate list), or both the first uni-prediction MV candidate list andthe second uni-prediction MV candidate list. In general, video encoder200 and video decoder 300 may use all of the MV candidates from thefirst candidate list first. If the predetermined size (e.g., 10candidates) of the list is not full after adding all candidates from thefirst candidate list, then video encoder 200 and video decoder 300 mayadd MV candidates from the second candidate list until the finalcandidate list has reached the predetermined number of candidates. Ifthe list is still short after adding candidates from the secondcandidate lists, video encoder 200 and video decoder 300 may padcandidates to the final candidate list. In some examples, the additionof MV candidates from the first candidate list and the second candidatelist are subject to the pruning techniques described below.

In one example of the above, the size of the final GEO MV candidatelist, the size of the first uni-prediction MV candidate list, and thesize of the second uni-prediction MV candidate list are M, M1, and M2,respectively, where M is a pre-assigned positive integer. If M1<M, thenM1 uni-prediction MV candidates in the first uni-prediction MV candidatelist, and (M−M1) uni-prediction MV candidates in the seconduni-prediction MV candidate list are added into final the GEO MVcandidate list, subject to pruning. Otherwise, if M1≥M, then Muni-prediction MV candidates in the first uni-prediction MV candidatelist are added into the final GEO MV candidate list, and the candidatesfrom the second uni-prediction MV candidate list are not used.

Accordingly, in a further example of the disclosure, video encoder 200and video decoder 300 may be configured to construct a final geometricpartitioning mode motion vector candidate list using at least one of thetwo uni-prediction motion vector candidate lists, and code the block ofvideo data using uni-prediction and the final geometric partitioningmode motion vector candidate list.

Pruning of GEO MV Candidates

In this example, video encoder 200 and video decoder 300 may beconfigured to apply a pruning process to remove redundant GEO MVcandidates. For example, this pruning process may be applied whileconstructing the final GEO candidate list. Video encoder 200 and videodecoder 300 may be configured to compare an MV candidate to be added tothe final GEO MV candidate list to candidates already added to the finalGEO MV candidate list. Based on the comparison result, the consideredcandidate may not be added to the final GEO MV candidate list. Forexample, if the considered candidate is already in the final GEO MVcandidate list, the considered candidate to be added is not added. Inone example, video encoder 200 and video decoder 300 compares an i-thGEO MV candidate with all of the j-th GEO MV candidates, where j couldbe 0, 1, . . . , and i−1, to check if the i-th GEO MV candidate can bepruned from (e.g., removed from or not added to the list) the final GEOMV candidate list.

In a specific example, if all of the following conditions are true in atleast one of the j-th GEO MV candidates, video encode 200 and videodecoder 300 are configured to prune the i-th GEO MV candidate from thefinal GEO merge candidate list:

-   -   1. If the same reference picture list (i.e., either L0 or L1) is        used by the i-th GEO MV candidate and the j-th GEO MV candidate.        For example, L0 is used by the i-th GEO MV candidate and the        j-th GEO MV candidate. In another example, L1 is used by the        i-th GEO MV candidate and the j-th GEO MV candidate.    -   2. If the same reference picture list index is used by the i-th        GEO MV candidate and the j-th GEO MV candidate. For example, the        reference picture list index 0 is used by the i-th GEO MV        candidate and the j-th GEO MV candidate. In another example, the        reference picture list index 1 is used by the i-th GEO MV        candidate and the j-th GEO MV candidate.    -   3. If the absolute value of a horizontal MV difference between        the i-th GEO MV candidate and the j-th GEO MV candidate is no        greater than a pre-defined MV difference threshold Tx, and the        absolute value of a vertical MV difference between the i-th GEO        MV candidate and the j-th GEO MV candidate is no greater than        the pre-defined MV difference threshold Ty (both L0 MVs and L1        MVs are checked), where Tx and Ty could be any positive        pre-assigned value, e.g. ¼, ½, and 1. Tx and Ty values may be        equal.

In one example, the pruning process for a first candidate list mayinclude removing a first candidate from the first candidate list basedon the first candidate having the same reference picture list as anothercandidate in the first candidate list, the first candidate having thesame reference picture list index as another candidate in the firstcandidate list, and the first candidate having a horizontal and verticalmotion vector difference from another candidate in the first candidatelist that is not greater than a threshold. Likewise, performing thesecond pruning process on the second candidate list may include removinga second candidate from the second candidate list based on the secondcandidate having the same reference picture list as another candidate inthe first candidate list or the second candidate list, the secondcandidate having the same reference picture list index as anothercandidate in the first candidate list or the second candidate list, andthe second candidate having a horizontal and vertical motion vectordifference from another candidate in the first candidate list or thesecond candidate list that is not greater than the threshold.

If combined with techniques described above for candidate listconstruction, the pruning process can be applied to the first candidatelist and the second candidate list independently. In one example, thepruning is done before the final GEO MV candidate list is constructedfrom those lists. In other words, the i-th GEO MV candidate in the firstuni-prediction MV candidate list is compared with the j-th GEO MVcandidates in the first uni-prediction MV candidate list, where j=0, 1,. . . , i−1, and the m-th GEO MV candidate in the second uni-predictionMV candidate list is compared with the n-th GEO MV candidates in thesecond uni-prediction MV candidate list, where n=0, 1, . . . , m−1.

In another example, video encoder 200 and video decoder 300 may apply apruning process to the first uni-prediction MV candidate list and thesecond uni-prediction MV candidate list jointly. In other words, thei-th GEO MV candidate in the first uni-prediction MV candidate list iscompared with the j-th GEO MV candidates in the first uni-prediction MVcandidate list, where j=0, 1, . . . , i−1, and the m-th GEO MV candidatein the second uni-prediction MV candidate list is compared with the j-thGEO MV candidates in the first uni-prediction MV candidate list, wherej=0, 1, . . . , M1−1, and is also compared with the n-th GEO MVcandidates in the second uni-prediction MV candidate list, where n=0, 1,. . . , m−1.

In one example, the thresholds Tx and Ty may be adaptive valuesdependent on block sizes. In one example, Tx and Ty are equal to T1 ifthe number of samples in the current coding block is greater than apre-defined positive integer N1. Otherwise, Tx and Ty are equal to T2 ifthe number of samples in the current coding block is greater than apre-defined positive integer N2 and smaller than or equal to N1.Otherwise, Tx and Ty are equal to T3 if the number of samples in thecurrent coding block is greater than a pre-defined positive integer N3and smaller than or equal to N2. Otherwise, Tx and Ty are equal to T4.Note that N1>N2>N3.

In one example, the values of Tx and Ty may be adaptive values dependenton the modes selected in the GEO coding block. In one example, Tx and Tyare equal to T1 if template matching GEO mode is used in the currentblock. Otherwise, Tx and Ty are equal to T2 if MMVD GEO mode isselected. Otherwise, Tx and Ty are equal to T3 if regular GEO mode isselected. Note that T1, T2, T3, and T4 mentioned above are positivevalues.

In another example for the conditions of the pruning process, a pictureorder count (POC) can be used to identify if the reference picture isthe same for both the i-th GEO MV candidate and the j-th GEO MVcandidate. Specifically, if all of the following conditions are true inat least one of the j-th GEO MV candidates, the i-th GEO MV candidate ispruned from the final GEO merge candidate list:

-   -   1. If the picture with the same POC value is referenced by the        i-th GEO MV candidate and the j-th GEO MV candidate.    -   2. If the same reference picture list index is used by the i-th        GEO MV candidate and the j-th GEO MV candidate. For example, the        reference picture list index 0 is used by the i-th GEO MV        candidate and the j-th GEO MV candidate. In another example, the        reference picture list index 1 is used by the i-th GEO MV        candidate and the j-th GEO MV candidate.

In another example of the disclosure, video encoder 200 and videodecoder 300 may be configured to operate according to constraintsapplied to the pruning process to only enable the pruning for some GEOMV candidates. One example is that video encoder 200 and video decoder300 are configured to only apply the pruning to the first P candidatesin a GEO candidates list, where P is smaller than the size of the list.In another example, the pruning process is only applied to the first Qcandidates that are pruned from (reduced from, or not added to) thecandidate list, where Q is smaller than the size of the list.

In general, in one example, video encoder 200 and video decoder 300 maybe configured to perform a pruning process on the final geometricpartitioning mode motion vector candidate list. In another example,video encoder 200 and video decoder 300 may be configured to perform apruning process on the two uni-prediction motion vector candidate lists(e.g., the first uni-prediction MV candidate list and the seconduni-prediction MV candidate list).

Uni-Prediction Zero GEO MV Candidates

In this example of the disclosure, video encoder 200 and video decoder300 are configured to pad uni-prediction MV candidates into the finalGEO MV candidate list if the final GEO MV candidate list is not full,i.e., the number of candidates is smaller than M. The addeduni-prediction MV candidates include interleaved list 0 MV candidatesand list 1 MV candidates. The x and y components of the MV can bepredefined fixed values. The reference indexes for the padded MVcandidates can be predefined fixed values or loop over the availablevalues.

One example is described as follows: Set an initial value for refListIdxas −1. If the i-th candidate in the final GEO MV candidate list isempty, a zero MV with the List X and refListIdx is padded, where X isset to be the parity of i, where parity=i & 1, and refListIdx is set tobe (refListIdx+1).

Suppose the maximum number of reference indexes, maxNumRefIdx, is set asfollows: If slice is B-slice, maxNumRefIdx is equal to min(the number ofreference indexes in REF_PIC_LIST_0, the number of reference indexes inREF_PIC_LIST_1); Otherwise, maxNumRefIdx is equal to the number ofreference indexes in REF_PIC_LIST_0.

If refListIdx is equal to maxNumRefIdx−1 after one candidate padding isfinished, the value of refListIdx is reset to be −1.

In general, video encoder 200 and video decoder 300 may be configured toadd one or more zero motion vector candidates to the final geometricpartitioning mode motion vector candidate list if a size of the finalgeometric partitioning mode motion vector candidate list is less than athreshold.

FIG. 4 is a block diagram illustrating an example video encoder 200 thatmay perform the techniques of this disclosure. FIG. 4 is provided forpurposes of explanation and should not be considered limiting of thetechniques as broadly exemplified and described in this disclosure. Forpurposes of explanation, this disclosure describes video encoder 200according to the techniques of VVC (ITU-T H.266, under development), andHEVC (ITU-T H.265). However, the techniques of this disclosure may beperformed by video encoding devices that are configured to other videocoding standards and video coding formats, such as AV1 and successors tothe AV1 video coding format.

In the example of FIG. 4 , video encoder 200 includes video data memory230, mode selection unit 202, residual generation unit 204, transformprocessing unit 206, quantization unit 208, inverse quantization unit210, inverse transform processing unit 212, reconstruction unit 214,filter unit 216, decoded picture buffer (DPB) 218, and entropy encodingunit 220. Any or all of video data memory 230, mode selection unit 202,residual generation unit 204, transform processing unit 206,quantization unit 208, inverse quantization unit 210, inverse transformprocessing unit 212, reconstruction unit 214, filter unit 216, DPB 218,and entropy encoding unit 220 may be implemented in one or moreprocessors or in processing circuitry. For instance, the units of videoencoder 200 may be implemented as one or more circuits or logic elementsas part of hardware circuitry, or as part of a processor, ASIC, or FPGA.Moreover, video encoder 200 may include additional or alternativeprocessors or processing circuitry to perform these and other functions.

Video data memory 230 may store video data to be encoded by thecomponents of video encoder 200. Video encoder 200 may receive the videodata stored in video data memory 230 from, for example, video source 104(FIG. 1 ). DPB 218 may act as a reference picture memory that storesreference video data for use in prediction of subsequent video data byvideo encoder 200. Video data memory 230 and DPB 218 may be formed byany of a variety of memory devices, such as dynamic random access memory(DRAM), including synchronous DRAM (SDRAM), magnetoresistive RAM (MRAM),resistive RAM (RRAM), or other types of memory devices. Video datamemory 230 and DPB 218 may be provided by the same memory device orseparate memory devices. In various examples, video data memory 230 maybe on-chip with other components of video encoder 200, as illustrated,or off-chip relative to those components.

In this disclosure, reference to video data memory 230 should not beinterpreted as being limited to memory internal to video encoder 200,unless specifically described as such, or memory external to videoencoder 200, unless specifically described as such. Rather, reference tovideo data memory 230 should be understood as reference memory thatstores video data that video encoder 200 receives for encoding (e.g.,video data for a current block that is to be encoded). Memory 106 ofFIG. 1 may also provide temporary storage of outputs from the variousunits of video encoder 200.

The various units of FIG. 4 are illustrated to assist with understandingthe operations performed by video encoder 200. The units may beimplemented as fixed-function circuits, programmable circuits, or acombination thereof. Fixed-function circuits refer to circuits thatprovide particular functionality, and are preset on the operations thatcan be performed. Programmable circuits refer to circuits that can beprogrammed to perform various tasks, and provide flexible functionalityin the operations that can be performed. For instance, programmablecircuits may execute software or firmware that cause the programmablecircuits to operate in the manner defined by instructions of thesoftware or firmware. Fixed-function circuits may execute softwareinstructions (e.g., to receive parameters or output parameters), but thetypes of operations that the fixed-function circuits perform aregenerally immutable. In some examples, one or more of the units may bedistinct circuit blocks (fixed-function or programmable), and in someexamples, one or more of the units may be integrated circuits.

Video encoder 200 may include arithmetic logic units (ALUs), elementaryfunction units (EFUs), digital circuits, analog circuits, and/orprogrammable cores, formed from programmable circuits. In examples wherethe operations of video encoder 200 are performed using softwareexecuted by the programmable circuits, memory 106 (FIG. 1 ) may storethe instructions (e.g., object code) of the software that video encoder200 receives and executes, or another memory within video encoder 200(not shown) may store such instructions.

Video data memory 230 is configured to store received video data. Videoencoder 200 may retrieve a picture of the video data from video datamemory 230 and provide the video data to residual generation unit 204and mode selection unit 202. Video data in video data memory 230 may beraw video data that is to be encoded.

Mode selection unit 202 includes a motion estimation unit 222, a motioncompensation unit 224, and an intra-prediction unit 226. Mode selectionunit 202 may include additional functional units to perform videoprediction in accordance with other prediction modes. As examples, modeselection unit 202 may include a palette unit, an intra-block copy unit(which may be part of motion estimation unit 222 and/or motioncompensation unit 224), an affine unit, a linear model (LM) unit, or thelike.

Mode selection unit 202 generally coordinates multiple encoding passesto test combinations of encoding parameters and resultingrate-distortion values for such combinations. The encoding parametersmay include partitioning of CTUs into CUs, prediction modes for the CUs,transform types for residual data of the CUs, quantization parametersfor residual data of the CUs, and so on. Mode selection unit 202 mayultimately select the combination of encoding parameters havingrate-distortion values that are better than the other testedcombinations.

Video encoder 200 may partition a picture retrieved from video datamemory 230 into a series of CTUs, and encapsulate one or more CTUswithin a slice. Mode selection unit 202 may partition a CTU of thepicture in accordance with a tree structure, such as the MTT structure,QTBT structure. superblock structure, or the quadtree structuredescribed above. As described above, video encoder 200 may form one ormore CUs from partitioning a CTU according to the tree structure. Such aCU may also be referred to generally as a “video block” or “block.”

In general, mode selection unit 202 also controls the components thereof(e.g., motion estimation unit 222, motion compensation unit 224, andintra-prediction unit 226) to generate a prediction block for a currentblock (e.g., a current CU, or in HEVC, the overlapping portion of a PUand a TU). For inter-prediction of a current block, motion estimationunit 222 may perform a motion search to identify one or more closelymatching reference blocks in one or more reference pictures (e.g., oneor more previously coded pictures stored in DPB 218). In particular,motion estimation unit 222 may calculate a value representative of howsimilar a potential reference block is to the current block, e.g.,according to sum of absolute difference (SAD), sum of squareddifferences (SSD), mean absolute difference (MAD), mean squareddifferences (MSD), or the like. Motion estimation unit 222 may generallyperform these calculations using sample-by-sample differences betweenthe current block and the reference block being considered. Motionestimation unit 222 may identify a reference block having a lowest valueresulting from these calculations, indicating a reference block thatmost closely matches the current block.

Motion estimation unit 222 may form one or more motion vectors (MVs)that defines the positions of the reference blocks in the referencepictures relative to the position of the current block in a currentpicture. Motion estimation unit 222 may then provide the motion vectorsto motion compensation unit 224. For example, for uni-directionalinter-prediction, motion estimation unit 222 may provide a single motionvector, whereas for bi-directional inter-prediction, motion estimationunit 222 may provide two motion vectors. Motion compensation unit 224may then generate a prediction block using the motion vectors. Forexample, motion compensation unit 224 may retrieve data of the referenceblock using the motion vector. As another example, if the motion vectorhas fractional sample precision, motion compensation unit 224 mayinterpolate values for the prediction block according to one or moreinterpolation filters. Moreover, for bi-directional inter-prediction,motion compensation unit 224 may retrieve data for two reference blocksidentified by respective motion vectors and combine the retrieved data,e.g., through sample-by-sample averaging or weighted averaging.

When operating according to the AV1 video coding format, motionestimation unit 222 and motion compensation unit 224 may be configuredto encode coding blocks of video data (e.g., both luma and chroma codingblocks) using translational motion compensation, affine motioncompensation, overlapped block motion compensation (OBMC), and/orcompound inter-intra prediction.

As another example, for intra-prediction, or intra-prediction coding,intra-prediction unit 226 may generate the prediction block from samplesneighboring the current block. For example, for directional modes,intra-prediction unit 226 may generally mathematically combine values ofneighboring samples and populate these calculated values in the defineddirection across the current block to produce the prediction block. Asanother example, for DC mode, intra-prediction unit 226 may calculate anaverage of the neighboring samples to the current block and generate theprediction block to include this resulting average for each sample ofthe prediction block.

When operating according to the AV1 video coding format, intraprediction unit 226 may be configured to encode coding blocks of videodata (e.g., both luma and chroma coding blocks) using directional intraprediction, non-directional intra prediction, recursive filter intraprediction, chroma-from-luma (CFL) prediction, intra block copy (IBC),and/or color palette mode. Mode selection unit 202 may includeadditional functional units to perform video prediction in accordancewith other prediction modes.

Mode selection unit 202 provides the prediction block to residualgeneration unit 204. Residual generation unit 204 receives a raw,unencoded version of the current block from video data memory 230 andthe prediction block from mode selection unit 202. Residual generationunit 204 calculates sample-by-sample differences between the currentblock and the prediction block. The resulting sample-by-sampledifferences define a residual block for the current block. In someexamples, residual generation unit 204 may also determine differencesbetween sample values in the residual block to generate a residual blockusing residual differential pulse code modulation (RDPCM). In someexamples, residual generation unit 204 may be formed using one or moresubtractor circuits that perform binary subtraction.

In examples where mode selection unit 202 partitions CUs into PUs, eachPU may be associated with a luma prediction unit and correspondingchroma prediction units. Video encoder 200 and video decoder 300 maysupport PUs having various sizes. As indicated above, the size of a CUmay refer to the size of the luma coding block of the CU and the size ofa PU may refer to the size of a luma prediction unit of the PU. Assumingthat the size of a particular CU is 2N×2N, video encoder 200 may supportPU sizes of 2N×2N or N×N for intra prediction, and symmetric PU sizes of2N×2N, 2N×N, N×2N, N×N, or similar for inter prediction. Video encoder200 and video decoder 300 may also support asymmetric partitioning forPU sizes of 2N×nU, 2N×nD, nL×2N, and nR×2N for inter prediction.

In examples where mode selection unit 202 does not further partition aCU into PUs, each CU may be associated with a luma coding block andcorresponding chroma coding blocks. As above, the size of a CU may referto the size of the luma coding block of the CU. The video encoder 200and video decoder 300 may support CU sizes of 2N×2N, 2N×N, or N×2N.

For other video coding techniques such as an intra-block copy modecoding, an affine-mode coding, and linear model (LM) mode coding, assome examples, mode selection unit 202, via respective units associatedwith the coding techniques, generates a prediction block for the currentblock being encoded. In some examples, such as palette mode coding, modeselection unit 202 may not generate a prediction block, and insteadgenerate syntax elements that indicate the manner in which toreconstruct the block based on a selected palette. In such modes, modeselection unit 202 may provide these syntax elements to entropy encodingunit 220 to be encoded.

As described above, residual generation unit 204 receives the video datafor the current block and the corresponding prediction block. Residualgeneration unit 204 then generates a residual block for the currentblock. To generate the residual block, residual generation unit 204calculates sample-by-sample differences between the prediction block andthe current block.

Transform processing unit 206 applies one or more transforms to theresidual block to generate a block of transform coefficients (referredto herein as a “transform coefficient block”). Transform processing unit206 may apply various transforms to a residual block to form thetransform coefficient block. For example, transform processing unit 206may apply a discrete cosine transform (DCT), a directional transform, aKarhunen-Loeve transform (KLT), or a conceptually similar transform to aresidual block. In some examples, transform processing unit 206 mayperform multiple transforms to a residual block, e.g., a primarytransform and a secondary transform, such as a rotational transform. Insome examples, transform processing unit 206 does not apply transformsto a residual block.

When operating according to AV1, transform processing unit 206 may applyone or more transforms to the residual block to generate a block oftransform coefficients (referred to herein as a “transform coefficientblock”). Transform processing unit 206 may apply various transforms to aresidual block to form the transform coefficient block. For example,transform processing unit 206 may apply a horizontal/vertical transformcombination that may include a discrete cosine transform (DCT), anasymmetric discrete sine transform (ADST), a flipped ADST (e.g., an ADSTin reverse order), and an identity transform (IDTX). When using anidentity transform, the transform is skipped in one of the vertical orhorizontal directions. In some examples, transform processing may beskipped.

Quantization unit 208 may quantize the transform coefficients in atransform coefficient block, to produce a quantized transformcoefficient block. Quantization unit 208 may quantize transformcoefficients of a transform coefficient block according to aquantization parameter (QP) value associated with the current block.Video encoder 200 (e.g., via mode selection unit 202) may adjust thedegree of quantization applied to the transform coefficient blocksassociated with the current block by adjusting the QP value associatedwith the CU. Quantization may introduce loss of information, and thus,quantized transform coefficients may have lower precision than theoriginal transform coefficients produced by transform processing unit206.

Inverse quantization unit 210 and inverse transform processing unit 212may apply inverse quantization and inverse transforms to a quantizedtransform coefficient block, respectively, to reconstruct a residualblock from the transform coefficient block. Reconstruction unit 214 mayproduce a reconstructed block corresponding to the current block (albeitpotentially with some degree of distortion) based on the reconstructedresidual block and a prediction block generated by mode selection unit202. For example, reconstruction unit 214 may add samples of thereconstructed residual block to corresponding samples from theprediction block generated by mode selection unit 202 to produce thereconstructed block.

Filter unit 216 may perform one or more filter operations onreconstructed blocks. For example, filter unit 216 may performdeblocking operations to reduce blockiness artifacts along edges of CUs.Operations of filter unit 216 may be skipped, in some examples.

When operating according to AV1, filter unit 216 may perform one or morefilter operations on reconstructed blocks. For example, filter unit 216may perform deblocking operations to reduce blockiness artifacts alongedges of CUs. In other examples, filter unit 216 may apply a constraineddirectional enhancement filter (CDEF), which may be applied afterdeblocking, and may include the application of non-separable,non-linear, low-pass directional filters based on estimated edgedirections. Filter unit 216 may also include a loop restoration filter,which is applied after CDEF, and may include a separable symmetricnormalized Wiener filter or a dual self-guided filter.

Video encoder 200 stores reconstructed blocks in DPB 218. For instance,in examples where operations of filter unit 216 are not performed,reconstruction unit 214 may store reconstructed blocks to DPB 218. Inexamples where operations of filter unit 216 are performed, filter unit216 may store the filtered reconstructed blocks to DPB 218. Motionestimation unit 222 and motion compensation unit 224 may retrieve areference picture from DPB 218, formed from the reconstructed (andpotentially filtered) blocks, to inter-predict blocks of subsequentlyencoded pictures. In addition, intra-prediction unit 226 may usereconstructed blocks in DPB 218 of a current picture to intra-predictother blocks in the current picture.

In general, entropy encoding unit 220 may entropy encode syntax elementsreceived from other functional components of video encoder 200. Forexample, entropy encoding unit 220 may entropy encode quantizedtransform coefficient blocks from quantization unit 208. As anotherexample, entropy encoding unit 220 may entropy encode prediction syntaxelements (e.g., motion information for inter-prediction or intra-modeinformation for intra-prediction) from mode selection unit 202. Entropyencoding unit 220 may perform one or more entropy encoding operations onthe syntax elements, which are another example of video data, togenerate entropy-encoded data. For example, entropy encoding unit 220may perform a context-adaptive variable length coding (CAVLC) operation,a CABAC operation, a variable-to-variable (V2V) length coding operation,a syntax-based context-adaptive binary arithmetic coding (SBAC)operation, a Probability Interval Partitioning Entropy (PIPE) codingoperation, an Exponential-Golomb encoding operation, or another type ofentropy encoding operation on the data. In some examples, entropyencoding unit 220 may operate in bypass mode where syntax elements arenot entropy encoded.

Video encoder 200 may output a bitstream that includes the entropyencoded syntax elements needed to reconstruct blocks of a slice orpicture. In particular, entropy encoding unit 220 may output thebitstream.

In accordance with AV1, entropy encoding unit 220 may be configured as asymbol-to-symbol adaptive multi-symbol arithmetic coder. A syntaxelement in AV1 includes an alphabet of N elements, and a context (e.g.,probability model) includes a set of N probabilities. Entropy encodingunit 220 may store the probabilities as n-bit (e.g., 15-bit) cumulativedistribution functions (CDFs). Entropy encoding unit 22 may performrecursive scaling, with an update factor based on the alphabet size, toupdate the contexts.

The operations described above are described with respect to a block.Such description should be understood as being operations for a lumacoding block and/or chroma coding blocks. As described above, in someexamples, the luma coding block and chroma coding blocks are luma andchroma components of a CU. In some examples, the luma coding block andthe chroma coding blocks are luma and chroma components of a PU.

In some examples, operations performed with respect to a luma codingblock need not be repeated for the chroma coding blocks. As one example,operations to identify a motion vector (MV) and reference picture for aluma coding block need not be repeated for identifying a MV andreference picture for the chroma blocks. Rather, the MV for the lumacoding block may be scaled to determine the MV for the chroma blocks,and the reference picture may be the same. As another example, theintra-prediction process may be the same for the luma coding block andthe chroma coding blocks.

Video encoder 200 represents an example of a device configured to encodevideo data including a memory configured to store video data, and one ormore processing units implemented in circuitry and configured todetermine a partitioning for a block of video data using geometricpartitioning mode, construct two uni-prediction motion vector candidatelists for the block of video data, and encode the block of video datausing uni-prediction based on at least one of the two uni-predictionmotion vector candidate lists.

FIG. 5 is a block diagram illustrating an example video decoder 300 thatmay perform the techniques of this disclosure. FIG. 5 is provided forpurposes of explanation and is not limiting on the techniques as broadlyexemplified and described in this disclosure. For purposes ofexplanation, this disclosure describes video decoder 300 according tothe techniques of VVC (ITU-T H.266, under development), and HEVC (ITU-TH.265). However, the techniques of this disclosure may be performed byvideo coding devices that are configured to other video codingstandards.

In the example of FIG. 5 , video decoder 300 includes coded picturebuffer (CPB) memory 320, entropy decoding unit 302, predictionprocessing unit 304, inverse quantization unit 306, inverse transformprocessing unit 308, reconstruction unit 310, filter unit 312, anddecoded picture buffer (DPB) 314. Any or all of CPB memory 320, entropydecoding unit 302, prediction processing unit 304, inverse quantizationunit 306, inverse transform processing unit 308, reconstruction unit310, filter unit 312, and DPB 314 may be implemented in one or moreprocessors or in processing circuitry. For instance, the units of videodecoder 300 may be implemented as one or more circuits or logic elementsas part of hardware circuitry, or as part of a processor, ASIC, or FPGA.Moreover, video decoder 300 may include additional or alternativeprocessors or processing circuitry to perform these and other functions.

Prediction processing unit 304 includes motion compensation unit 316 andintra-prediction unit 318. Prediction processing unit 304 may includeadditional units to perform prediction in accordance with otherprediction modes. As examples, prediction processing unit 304 mayinclude a palette unit, an intra-block copy unit (which may form part ofmotion compensation unit 316), an affine unit, a linear model (LM) unit,or the like. In other examples, video decoder 300 may include more,fewer, or different functional components.

When operating according to AV1, compensation unit 316 may be configuredto decode coding blocks of video data (e.g., both luma and chroma codingblocks) using translational motion compensation, affine motioncompensation, OBMC, and/or compound inter-intra prediction, as describedabove. Intra prediction unit 318 may be configured to decode codingblocks of video data (e.g., both luma and chroma coding blocks) usingdirectional intra prediction, non-directional intra prediction,recursive filter intra prediction, CFL, intra block copy (IBC), and/orcolor palette mode, as described above.

CPB memory 320 may store video data, such as an encoded video bitstream,to be decoded by the components of video decoder 300. The video datastored in CPB memory 320 may be obtained, for example, fromcomputer-readable medium 110 (FIG. 1 ). CPB memory 320 may include a CPBthat stores encoded video data (e.g., syntax elements) from an encodedvideo bitstream. Also, CPB memory 320 may store video data other thansyntax elements of a coded picture, such as temporary data representingoutputs from the various units of video decoder 300. DPB 314 generallystores decoded pictures, which video decoder 300 may output and/or useas reference video data when decoding subsequent data or pictures of theencoded video bitstream. CPB memory 320 and DPB 314 may be formed by anyof a variety of memory devices, such as DRAM, including SDRAM, MRAM,RRAM, or other types of memory devices. CPB memory 320 and DPB 314 maybe provided by the same memory device or separate memory devices. Invarious examples, CPB memory 320 may be on-chip with other components ofvideo decoder 300, or off-chip relative to those components.

Additionally or alternatively, in some examples, video decoder 300 mayretrieve coded video data from memory 120 (FIG. 1 ). That is, memory 120may store data as discussed above with CPB memory 320. Likewise, memory120 may store instructions to be executed by video decoder 300, whensome or all of the functionality of video decoder 300 is implemented insoftware to be executed by processing circuitry of video decoder 300.

The various units shown in FIG. 5 are illustrated to assist withunderstanding the operations performed by video decoder 300. The unitsmay be implemented as fixed-function circuits, programmable circuits, ora combination thereof. Similar to FIG. 4 , fixed-function circuits referto circuits that provide particular functionality, and are preset on theoperations that can be performed. Programmable circuits refer tocircuits that can be programmed to perform various tasks, and provideflexible functionality in the operations that can be performed. Forinstance, programmable circuits may execute software or firmware thatcause the programmable circuits to operate in the manner defined byinstructions of the software or firmware. Fixed-function circuits mayexecute software instructions (e.g., to receive parameters or outputparameters), but the types of operations that the fixed-functioncircuits perform are generally immutable. In some examples, one or moreof the units may be distinct circuit blocks (fixed-function orprogrammable), and in some examples, one or more of the units may beintegrated circuits.

Video decoder 300 may include ALUs, EFUs, digital circuits, analogcircuits, and/or programmable cores formed from programmable circuits.In examples where the operations of video decoder 300 are performed bysoftware executing on the programmable circuits, on-chip or off-chipmemory may store instructions (e.g., object code) of the software thatvideo decoder 300 receives and executes.

Entropy decoding unit 302 may receive encoded video data from the CPBand entropy decode the video data to reproduce syntax elements.Prediction processing unit 304, inverse quantization unit 306, inversetransform processing unit 308, reconstruction unit 310, and filter unit312 may generate decoded video data based on the syntax elementsextracted from the bitstream.

In general, video decoder 300 reconstructs a picture on a block-by-blockbasis. Video decoder 300 may perform a reconstruction operation on eachblock individually (where the block currently being reconstructed, i.e.,decoded, may be referred to as a “current block”).

Entropy decoding unit 302 may entropy decode syntax elements definingquantized transform coefficients of a quantized transform coefficientblock, as well as transform information, such as a quantizationparameter (QP) and/or transform mode indication(s). Inverse quantizationunit 306 may use the QP associated with the quantized transformcoefficient block to determine a degree of quantization and, likewise, adegree of inverse quantization for inverse quantization unit 306 toapply. Inverse quantization unit 306 may, for example, perform a bitwiseleft-shift operation to inverse quantize the quantized transformcoefficients. Inverse quantization unit 306 may thereby form a transformcoefficient block including transform coefficients.

After inverse quantization unit 306 forms the transform coefficientblock, inverse transform processing unit 308 may apply one or moreinverse transforms to the transform coefficient block to generate aresidual block associated with the current block. For example, inversetransform processing unit 308 may apply an inverse DCT, an inverseinteger transform, an inverse Karhunen-Loeve transform (KLT), an inverserotational transform, an inverse directional transform, or anotherinverse transform to the transform coefficient block.

Furthermore, prediction processing unit 304 generates a prediction blockaccording to prediction information syntax elements that were entropydecoded by entropy decoding unit 302. For example, if the predictioninformation syntax elements indicate that the current block isinter-predicted, motion compensation unit 316 may generate theprediction block. In this case, the prediction information syntaxelements may indicate a reference picture in DPB 314 from which toretrieve a reference block, as well as a motion vector identifying alocation of the reference block in the reference picture relative to thelocation of the current block in the current picture. Motioncompensation unit 316 may generally perform the inter-prediction processin a manner that is substantially similar to that described with respectto motion compensation unit 224 (FIG. 4 ).

As another example, if the prediction information syntax elementsindicate that the current block is intra-predicted, intra-predictionunit 318 may generate the prediction block according to anintra-prediction mode indicated by the prediction information syntaxelements. Again, intra-prediction unit 318 may generally perform theintra-prediction process in a manner that is substantially similar tothat described with respect to intra-prediction unit 226 (FIG. 4 ).Intra-prediction unit 318 may retrieve data of neighboring samples tothe current block from DPB 314.

Reconstruction unit 310 may reconstruct the current block using theprediction block and the residual block. For example, reconstructionunit 310 may add samples of the residual block to corresponding samplesof the prediction block to reconstruct the current block.

Filter unit 312 may perform one or more filter operations onreconstructed blocks. For example, filter unit 312 may performdeblocking operations to reduce blockiness artifacts along edges of thereconstructed blocks. Operations of filter unit 312 are not necessarilyperformed in all examples.

Video decoder 300 may store the reconstructed blocks in DPB 314. Forinstance, in examples where operations of filter unit 312 are notperformed, reconstruction unit 310 may store reconstructed blocks to DPB314. In examples where operations of filter unit 312 are performed,filter unit 312 may store the filtered reconstructed blocks to DPB 314.As discussed above, DPB 314 may provide reference information, such assamples of a current picture for intra-prediction and previously decodedpictures for subsequent motion compensation, to prediction processingunit 304. Moreover, video decoder 300 may output decoded pictures (e.g.,decoded video) from DPB 314 for subsequent presentation on a displaydevice, such as display device 118 of FIG. 1 .

In this manner, video decoder 300 represents an example of a videodecoding device including a memory configured to store video data, andone or more processing units implemented in circuitry and configured todetermine a partitioning for a block of video data using geometricpartitioning mode, construct two uni-prediction motion vector candidatelists for the block of video data, and decode the block of video datausing uni-prediction based on at least one of the two uni-predictionmotion vector candidate lists.

FIG. 6 is a flowchart illustrating an example method for encoding acurrent block in accordance with the techniques of this disclosure. Thecurrent block may comprise a current CU. Although described with respectto video encoder 200 (FIGS. 1 and 4 ), it should be understood thatother devices may be configured to perform a method similar to that ofFIG. 6 .

In this example, video encoder 200 initially predicts the current block(350). For example, video encoder 200 may form a prediction block forthe current block. Video encoder 200 may then calculate a residual blockfor the current block (352). To calculate the residual block, videoencoder 200 may calculate a difference between the original, unencodedblock and the prediction block for the current block. Video encoder 200may then transform the residual block and quantize transformcoefficients of the residual block (354). Next, video encoder 200 mayscan the quantized transform coefficients of the residual block (356).During the scan, or following the scan, video encoder 200 may entropyencode the transform coefficients (358). For example, video encoder 200may encode the transform coefficients using CAVLC or CABAC. Videoencoder 200 may then output the entropy encoded data of the block (360).

FIG. 7 is a flowchart illustrating an example method for decoding acurrent block of video data in accordance with the techniques of thisdisclosure. The current block may comprise a current CU. Althoughdescribed with respect to video decoder 300 (FIGS. 1 and 5 ), it shouldbe understood that other devices may be configured to perform a methodsimilar to that of FIG. 7 .

Video decoder 300 may receive entropy encoded data for the currentblock, such as entropy encoded prediction information and entropyencoded data for transform coefficients of a residual blockcorresponding to the current block (370). Video decoder 300 may entropydecode the entropy encoded data to determine prediction information forthe current block and to reproduce transform coefficients of theresidual block (372). Video decoder 300 may predict the current block(374), e.g., using an intra- or inter-prediction mode as indicated bythe prediction information for the current block, to calculate aprediction block for the current block. Video decoder 300 may theninverse scan the reproduced transform coefficients (376), to create ablock of quantized transform coefficients. Video decoder 300 may theninverse quantize the transform coefficients and apply an inversetransform to the transform coefficients to produce a residual block(378). Video decoder 300 may ultimately decode the current block bycombining the prediction block and the residual block (380).

FIG. 8 is a flowchart illustrating another example method for encoding acurrent block in accordance with the techniques of this disclosure. Thetechniques of FIG. 8 may be performed by one or more structuralcomponents of video encoder 200, including motion estimation unit 222and/or motion compensation unit 224 (FIG. 4 ).

In one example, video encoder 200 may be configured to determine apartitioning for the block of video data using geometric partitioningmode (800), construct two uni-prediction motion vector candidate listsfor the block of video data (802), and encode the block of video datausing uni-prediction based on at least one of the two uni-predictionmotion vector candidate lists to generate an encoded block of video data(804).

In one example, to construct two uni-prediction motion vector candidatelists for the block of video data, video encoder 200 is furtherconfigured to construct a first candidate list of the two uni-predictionmotion vector candidate lists, including interleaving first motionvector candidates from a first reference picture list with second motionvector candidates from a second reference picture list, and construct asecond candidate list of the two uni-prediction motion vector candidatelists, including interleaving the second motion vector candidates fromthe second reference picture list with the first motion vectorcandidates from the first reference picture list.

In another example, video encoder 200 is configured to perform a firstpruning process on the first candidate list, and perform a secondpruning process on the second candidate list.

FIG. 9 is a flowchart illustrating another example method for decoding acurrent block in accordance with the techniques of this disclosure. Thetechniques of FIG. 8 may be performed by one or more structuralcomponents of video decoder 300, including motion compensation unit 316(FIG. 5 ).

In one example, video decoder 300 is configured to determine apartitioning for the block of video data using geometric partitioningmode (900), construct two uni-prediction motion vector candidate listsfor the block of video data (902), and decode the block of video datausing uni-prediction based on at least one of the two uni-predictionmotion vector candidate lists to generate a decoded block of video data(904).

In one example, to construct two uni-prediction motion vector candidatelists for the block of video data, video decoder 300 is configured toconstruct a first candidate list of the two uni-prediction motion vectorcandidate lists, including interleaving first motion vector candidatesfrom a first reference picture list with second motion vector candidatesfrom a second reference picture list, and construct a second candidatelist of the two uni-prediction motion vector candidate lists, includinginterleaving the second motion vector candidates from the secondreference picture list with the first motion vector candidates from thefirst reference picture list.

In one example, to interleave first motion vector candidates from thefirst reference picture list with second motion vector candidates fromthe second reference picture list, video decoder 300 is configured toadd the first motion vector candidates and the second motion vectorcandidates to the first candidate list in an alternating fashion whereina candidate from the first motion vector candidates is added first.

In another example, to interleave second motion vector candidates fromthe second reference picture list with first motion vector candidatesfrom the first reference picture list, video decoder 300 is configuredto add the second motion vector candidates and the first motion vectorcandidates to the second candidate list in an alternating fashionwherein a candidate from the second motion vector candidates is addedfirst.

In another example, video decoder 300 is configured to perform a firstpruning process on the first candidate list, and perform a secondpruning process on the second candidate list. To perform the firstpruning process on the first candidate list, video decoder 300 may beconfigured to remove a first candidate from the first candidate listbased on the first candidate having the same reference picture list asanother candidate in the first candidate list, the first candidatehaving the same reference picture list index as another candidate in thefirst candidate list, and the first candidate having a horizontal andvertical motion vector difference from another candidate in the firstcandidate list that is not greater than a threshold. Likewise, toperform the second pruning process on the second candidate list, videodecoder 300 is configured to remove a second candidate from the secondcandidate list based on the second candidate having the same referencepicture list as another candidate in the first candidate list or thesecond candidate list, the second candidate having the same referencepicture list index as another candidate in the first candidate list orthe second candidate list, and the second candidate having a horizontaland vertical motion vector difference from another candidate in thefirst candidate list or the second candidate list that is not greaterthan the threshold.

In another example, video decoder 300 is configured to construct a finalgeometric partitioning mode motion vector candidate list using the firstcandidate list and the second candidate list. In one example, toconstruct the final geometric partitioning mode motion vector candidatelist using the first candidate list and the second candidate list, videodecoder 300 is configured to add the first motion vector candidates fromthe first candidate list to the final geometric partitioning mode motionvector candidate list, add, in the case that the final geometricpartitioning mode motion vector candidate list is less than apredetermined number of candidates after adding the first motion vectorcandidates, the second motion vector candidates from the secondcandidate list to the final geometric partitioning mode motion vectorcandidate list, and pad, in the case that the final geometricpartitioning mode motion vector candidate list is less than thepredetermined number of candidates after adding the first motion vectorcandidates and the second motion vector candidates, zero motion vectorcandidates to the final geometric partitioning mode motion vectorcandidate list. In another example, video decoder 300 is configured toperform a pruning process on the final geometric partitioning modemotion vector candidate list. To decode the block of video data usinguni-prediction, video decoder 300 is configured to decode the block ofvideo data using uni-prediction and the final geometric partitioningmode motion vector candidate list.

Other illustrative aspects of the disclosure are described below.

Aspect 1A—A method of coding video data, the method comprising:determining a partitioning for a block of video data using geometricpartitioning mode; constructing two uni-prediction motion vectorcandidate lists for the block of video data; and coding the block ofvideo data using uni-prediction based on at least one of the twouni-prediction motion vector candidate lists.

Aspect 2A—The method of Aspect 1A, further comprising: constructing afinal geometric partitioning mode motion vector candidate list using atleast one of the two uni-prediction motion vector candidate lists.

Aspect 3A—The method of Aspect 2A, wherein coding the block of videodata using uni-prediction comprises: coding the block of video datausing uni-prediction and the final geometric partitioning mode motionvector candidate list.

Aspect 4A—The method of Aspect 3A, further comprising: performing apruning process on the final geometric partitioning mode motion vectorcandidate list.

Aspect 5A—The method of any of Aspects 1A-4A, further comprising:performing a pruning process on the two uni-prediction motion vectorcandidate lists.

Aspect 6A—The method of Aspect 3A, further comprising: adding one ormore zero motion vector candidates to the final geometric partitioningmode motion vector candidate list if a size of the final geometricpartitioning mode motion vector candidate list is less than a threshold.

Aspect 7A—The method of any of Aspects 1A-6A, wherein coding comprisesdecoding.

Aspect 8A—The method of any of Aspects 1A-6A, wherein coding comprisesencoding.

Aspect 9A—A device for coding video data, the device comprising one ormore means for performing the method of any of Aspects 1A-8A.

Aspect 10A—The device of Aspect 9A, wherein the one or more meanscomprise one or more processors implemented in circuitry.

Aspect 11A—The device of any of Aspects 9A and 10A, further comprising amemory to store the video data.

Aspect 12A—The device of any of Aspects 9A-11A, further comprising adisplay configured to display decoded video data.

Aspect 13A—The device of any of Aspects 9A-12A, wherein the devicecomprises one or more of a camera, a computer, a mobile device, abroadcast receiver device, or a set-top box.

Aspect 14A—The device of any of Aspects 9A-13A, wherein the devicecomprises a video decoder.

Aspect 15A—The device of any of Aspects 9A-14A, wherein the devicecomprises a video encoder.

Aspect 16A—A computer-readable storage medium having stored thereoninstructions that, when executed, cause one or more processors toperform the method of any of Aspects 1A-8A.

Aspect 17A—A device for coding video data, the device comprising: meansfor determining a partitioning for a block of video data using geometricpartitioning mode; means for constructing two uni-prediction motionvector candidate lists for the block of video data; and means for codingthe block of video data using uni-prediction based on at least one ofthe two uni-prediction motion vector candidate lists.

Aspect 1B—A method of decoding video data, the method comprising:determining a partitioning for a block of video data using geometricpartitioning mode; constructing two uni-prediction motion vectorcandidate lists for the block of video data; and decoding the block ofvideo data using uni-prediction based on at least one of the twouni-prediction motion vector candidate lists to generate a decoded blockof video data.

Aspect 2B—The method of Aspect 1B, wherein constructing twouni-prediction motion vector candidate lists for the block of video datacomprises: constructing a first candidate list of the two uni-predictionmotion vector candidate lists, including interleaving first motionvector candidates from a first reference picture list with second motionvector candidates from a second reference picture list; and constructinga second candidate list of the two uni-prediction motion vectorcandidate lists, including interleaving the second motion vectorcandidates from the second reference picture list with the first motionvector candidates from the first reference picture list.

Aspect 3B—The method of Aspect 2B, wherein interleaving first motionvector candidates from the first reference picture list with secondmotion vector candidates from the second reference picture listcomprises adding the first motion vector candidates and the secondmotion vector candidates to the first candidate list in an alternatingfashion wherein a candidate from the first motion vector candidates isadded first.

Aspect 4B—The method of Aspect 2B, wherein interleaving second motionvector candidates from the second reference picture list with firstmotion vector candidates from the first reference picture list comprisesadding the second motion vector candidates and the first motion vectorcandidates to the second candidate list in an alternating fashionwherein a candidate from the second motion vector candidates is addedfirst.

Aspect 5B—The method of Aspect 2B, further comprising: performing afirst pruning process on the first candidate list; and performing asecond pruning process on the second candidate list.

Aspect 6B—The method of Aspect 5B, wherein performing the first pruningprocess on the first candidate list comprises: removing a firstcandidate from the first candidate list based on the first candidatehaving the same reference picture list as another candidate in the firstcandidate list, the first candidate having the same reference picturelist index as another candidate in the first candidate list, and thefirst candidate having a horizontal and vertical motion vectordifference from another candidate in the first candidate list that isnot greater than a threshold, and wherein performing the second pruningprocess on the second candidate list comprises: removing a secondcandidate from the second candidate list based on the second candidatehaving the same reference picture list as another candidate in the firstcandidate list or the second candidate list, the second candidate havingthe same reference picture list index as another candidate in the firstcandidate list or the second candidate list, and the second candidatehaving a horizontal and vertical motion vector difference from anothercandidate in the first candidate list or the second candidate list thatis not greater than the threshold.

Aspect 7B—The method of Aspect 2B, further comprising: constructing afinal geometric partitioning mode motion vector candidate list using thefirst candidate list and the second candidate list.

Aspect 8B—The method of Aspect 7B, wherein constructing the finalgeometric partitioning mode motion vector candidate list using the firstcandidate list and the second candidate list comprises: adding the firstmotion vector candidates from the first candidate list to the finalgeometric partitioning mode motion vector candidate list; adding, in thecase that the final geometric partitioning mode motion vector candidatelist is less than a predetermined number of candidates after adding thefirst motion vector candidates, the second motion vector candidates fromthe second candidate list to the final geometric partitioning modemotion vector candidate list; and padding, in the case that the finalgeometric partitioning mode motion vector candidate list is less thanthe predetermined number of candidates after adding the first motionvector candidates and the second motion vector candidates, zero motionvector candidates to the final geometric partitioning mode motion vectorcandidate list.

Aspect 9B—The method of Aspect 7B, further comprising: performing apruning process on the final geometric partitioning mode motion vectorcandidate list.

Aspect 10B—The method of Aspect 7B, wherein decoding the block of videodata using uni-prediction comprises: decoding the block of video datausing uni-prediction and the final geometric partitioning mode motionvector candidate list.

Aspect 11B—The method of Aspect 1B, further comprising: displaying apicture that includes the decoded block of video data.

Aspect 12B—An apparatus configured to decode video data, the apparatuscomprising: a memory configured to store a block of video data; and oneor more processors in communication with the memory, the one or moreprocessors configured to: determine a partitioning for the block ofvideo data using geometric partitioning mode; construct twouni-prediction motion vector candidate lists for the block of videodata; and decode the block of video data using uni-prediction based onat least one of the two uni-prediction motion vector candidate lists togenerate a decoded block of video data.

Aspect 13B—The apparatus of Aspect 12B, wherein to construct twouni-prediction motion vector candidate lists for the block of videodata, the one or more processors are further configured to: construct afirst candidate list of the two uni-prediction motion vector candidatelists, including interleaving first motion vector candidates from afirst reference picture list with second motion vector candidates from asecond reference picture list; and construct a second candidate list ofthe two uni-prediction motion vector candidate lists, includinginterleaving the second motion vector candidates from the secondreference picture list with the first motion vector candidates from thefirst reference picture list.

Aspect 14B—The apparatus of Aspect 13B, wherein to interleave firstmotion vector candidates from the first reference picture list withsecond motion vector candidates from the second reference picture list,the one or more processors are configured to add the first motion vectorcandidates and the second motion vector candidates to the firstcandidate list in an alternating fashion wherein a candidate from thefirst motion vector candidates is added first.

Aspect 15B—The apparatus of Aspect 13B, wherein to interleave secondmotion vector candidates from the second reference picture list withfirst motion vector candidates from the first reference picture list,the one or more processors are configured to add the second motionvector candidates and the first motion vector candidates to the secondcandidate list in an alternating fashion wherein a candidate from thesecond motion vector candidates is added first.

Aspect 16B—The apparatus of Aspect 13B, wherein the one or moreprocessors are further configured to: perform a first pruning process onthe first candidate list; and perform a second pruning process on thesecond candidate list.

Aspect 17B—The apparatus of Aspect 16B, wherein to perform the firstpruning process on the first candidate list, the one or more processorsare configured to: remove a first candidate from the first candidatelist based on the first candidate having the same reference picture listas another candidate in the first candidate list, the first candidatehaving the same reference picture list index as another candidate in thefirst candidate list, and the first candidate having a horizontal andvertical motion vector difference from another candidate in the firstcandidate list that is not greater than a threshold, and wherein toperform the second pruning process on the second candidate list, the oneor more processors are configured to: remove a second candidate from thesecond candidate list based on the second candidate having the samereference picture list as another candidate in the first candidate listor the second candidate list, the second candidate having the samereference picture list index as another candidate in the first candidatelist or the second candidate list, and the second candidate having ahorizontal and vertical motion vector difference from another candidatein the first candidate list or the second candidate list that is notgreater than the threshold.

Aspect 18B—The apparatus of Aspect 13B, wherein the one or moreprocessors are further configured to: construct a final geometricpartitioning mode motion vector candidate list using the first candidatelist and the second candidate list.

Aspect 19B—The apparatus of Aspect 18B, wherein to construct the finalgeometric partitioning mode motion vector candidate list using the firstcandidate list and the second candidate list, the one or more processorsare further configured to: add the first motion vector candidates fromthe first candidate list to the final geometric partitioning mode motionvector candidate list; add, in the case that the final geometricpartitioning mode motion vector candidate list is less than apredetermined number of candidates after adding the first motion vectorcandidates, the second motion vector candidates from the secondcandidate list to the final geometric partitioning mode motion vectorcandidate list; and pad, in the case that the final geometricpartitioning mode motion vector candidate list is less than thepredetermined number of candidates after adding the first motion vectorcandidates and the second motion vector candidates, zero motion vectorcandidates to the final geometric partitioning mode motion vectorcandidate list.

Aspect 20B—The apparatus of Aspect 19B, wherein the one or moreprocessors are further configured to: perform a pruning process on thefinal geometric partitioning mode motion vector candidate list.

Aspect 21B—The apparatus of Aspect 19B, wherein to decode the block ofvideo data using uni-prediction, the one or more processors are furtherconfigured to: decode the block of video data using uni-prediction andthe final geometric partitioning mode motion vector candidate list.

Aspect 22B—The apparatus of Aspect 12B, further comprising: a displayconfigured to display a picture that includes the decoded block of videodata.

Aspect 23B—A non-transitory computer-readable storage medium storinginstructions that, when executed, cause one or more processors of adevice configured to decode video data to: determine a partitioning forthe block of video data using geometric partitioning mode; construct twouni-prediction motion vector candidate lists for the block of videodata; and decode the block of video data using uni-prediction based onat least one of the two uni-prediction motion vector candidate lists togenerate a decoded block of video data.

Aspect 24B. The non-transitory computer-readable storage medium ofAspect 23B, wherein to construct two uni-prediction motion vectorcandidate lists for the block of video data, the instructions furthercause the one or more processors to: construct a first candidate list ofthe two uni-prediction motion vector candidate lists, includinginterleaving first motion vector candidates from a first referencepicture list with second motion vector candidates from a secondreference picture list; and construct a second candidate list of the twouni-prediction motion vector candidate lists, including interleaving thesecond motion vector candidates from the second reference picture listwith the first motion vector candidates from the first reference picturelist.

Aspect 25B—The non-transitory computer-readable storage medium of Aspect24B, wherein the instructions further cause the one or more processorsto: perform a first pruning process on the first candidate list; andperform a second pruning process on the second candidate list.

Aspect 26B—An apparatus configured to encode video data, the apparatuscomprising: a memory configured to store a block of video data; and oneor more processors in communication with the memory, the one or moreprocessors configured to: determine a partitioning for the block ofvideo data using geometric partitioning mode; construct twouni-prediction motion vector candidate lists for the block of videodata; and encode the block of video data using uni-prediction based onat least one of the two uni-prediction motion vector candidate lists togenerate an encoded block of video data.

Aspect 27B—The apparatus of Aspect 26B, wherein to construct twouni-prediction motion vector candidate lists for the block of videodata, the one or more processors are further configured to: construct afirst candidate list of the two uni-prediction motion vector candidatelists, including interleaving first motion vector candidates from afirst reference picture list with second motion vector candidates from asecond reference picture list; and construct a second candidate list ofthe two uni-prediction motion vector candidate lists, includinginterleaving the second motion vector candidates from the secondreference picture list with the first motion vector candidates from thefirst reference picture list.

Aspect 28B—The apparatus of Aspect 27B, wherein the one or moreprocessors are further configured to: perform a first pruning process onthe first candidate list; and perform a second pruning process on thesecond candidate list.

Aspect 1C—A method of decoding video data, the method comprising:determining a partitioning for a block of video data using geometricpartitioning mode; constructing two uni-prediction motion vectorcandidate lists for the block of video data; and decoding the block ofvideo data using uni-prediction based on at least one of the twouni-prediction motion vector candidate lists to generate a decoded blockof video data.

Aspect 2C—The method of Aspect 1C, wherein constructing twouni-prediction motion vector candidate lists for the block of video datacomprises: constructing a first candidate list of the two uni-predictionmotion vector candidate lists, including interleaving first motionvector candidates from a first reference picture list with second motionvector candidates from a second reference picture list; and constructinga second candidate list of the two uni-prediction motion vectorcandidate lists, including interleaving the second motion vectorcandidates from the second reference picture list with the first motionvector candidates from the first reference picture list.

Aspect 3C—The method of Aspect 2C, wherein interleaving first motionvector candidates from the first reference picture list with secondmotion vector candidates from the second reference picture listcomprises adding the first motion vector candidates and the secondmotion vector candidates to the first candidate list in an alternatingfashion wherein a candidate from the first motion vector candidates isadded first.

Aspect 4C—The method of any of Aspects 2C-3C, wherein interleavingsecond motion vector candidates from the second reference picture listwith first motion vector candidates from the first reference picturelist comprises adding the second motion vector candidates and the firstmotion vector candidates to the second candidate list in an alternatingfashion wherein a candidate from the second motion vector candidates isadded first.

Aspect 5C—The method of any of Aspects 2C-4C, further comprising:performing a first pruning process on the first candidate list; andperforming a second pruning process on the second candidate list.

Aspect 6C—The method of Aspect 5C, wherein performing the first pruningprocess on the first candidate list comprises: removing a firstcandidate from the first candidate list based on the first candidatehaving the same reference picture list as another candidate in the firstcandidate list, the first candidate having the same reference picturelist index as another candidate in the first candidate list, and thefirst candidate having a horizontal and vertical motion vectordifference from another candidate in the first candidate list that isnot greater than a threshold, and wherein performing the second pruningprocess on the second candidate list comprises: removing a secondcandidate from the second candidate list based on the second candidatehaving the same reference picture list as another candidate the firstcandidate list or in the second candidate list, the second candidatehaving the same reference picture list index as another candidate thefirst candidate list or in the second candidate list, and the secondcandidate having a horizontal and vertical motion vector difference fromanother candidate in the first candidate list or the second candidatelist that is not greater than the threshold.

Aspect 7C—The method of any of Aspects 2C-6C, further comprising:constructing a final geometric partitioning mode motion vector candidatelist using the first candidate list and the second candidate list.

Aspect 8C—The method of Aspect 7C, wherein constructing the finalgeometric partitioning mode motion vector candidate list using the firstcandidate list and the second candidate list comprises: adding the firstmotion vector candidates from the first candidate list to the finalgeometric partitioning mode motion vector candidate list; adding, in thecase that the final geometric partitioning mode motion vector candidatelist is less than a predetermined number of candidates after adding thefirst motion vector candidates, the second motion vector candidates fromthe second candidate list to the final geometric partitioning modemotion vector candidate list; and padding, in the case that the finalgeometric partitioning mode motion vector candidate list is less thanthe predetermined number of candidates after adding the first motionvector candidates and the second motion vector candidates, zero motionvector candidates to the final geometric partitioning mode motion vectorcandidate list.

Aspect 9C—The method of any of Aspects 7C-8C, further comprising:performing a pruning process on the final geometric partitioning modemotion vector candidate list.

Aspect 10C—The method of any of Aspects 7C-9C, wherein decoding theblock of video data using uni-prediction comprises: decoding the blockof video data using uni-prediction and the final geometric partitioningmode motion vector candidate list.

Aspect 11C—The method of any of Aspects 1C-10C, further comprising:displaying a picture that includes the decoded block of video data.

Aspect 12C—An apparatus configured to decode video data, the apparatuscomprising: a memory configured to store a block of video data; and oneor more processors in communication with the memory, the one or moreprocessors configured to: determine a partitioning for the block ofvideo data using geometric partitioning mode; construct twouni-prediction motion vector candidate lists for the block of videodata; and decode the block of video data using uni-prediction based onat least one of the two uni-prediction motion vector candidate lists togenerate a decoded block of video data.

Aspect 13C—The apparatus of Aspect 12C, wherein to construct twouni-prediction motion vector candidate lists for the block of videodata, the one or more processors are further configured to: construct afirst candidate list of the two uni-prediction motion vector candidatelists, including interleaving first motion vector candidates from afirst reference picture list with second motion vector candidates from asecond reference picture list; and construct a second candidate list ofthe two uni-prediction motion vector candidate lists, includinginterleaving the second motion vector candidates from the secondreference picture list with the first motion vector candidates from thefirst reference picture list.

Aspect 14C—The apparatus of Aspect 13C, wherein to interleave firstmotion vector candidates from the first reference picture list withsecond motion vector candidates from the second reference picture list,the one or more processors are configured to add the first motion vectorcandidates and the second motion vector candidates to the firstcandidate list in an alternating fashion wherein a candidate from thefirst motion vector candidates is added first.

Aspect 15C—The apparatus of any of Aspects 13C-14C, wherein tointerleave second motion vector candidates from the second referencepicture list with first motion vector candidates from the firstreference picture list, the one or more processors are configured to addthe second motion vector candidates and the first motion vectorcandidates to the second candidate list in an alternating fashionwherein a candidate from the second motion vector candidates is addedfirst.

Aspect 16C—The apparatus of any of Aspects 13C-15C, wherein the one ormore processors are further configured to: perform a first pruningprocess on the first candidate list; and perform a second pruningprocess on the second candidate list.

Aspect 17C—The apparatus of Aspect 16C, wherein to perform the firstpruning process on the first candidate list, the one or more processorsare configured to: remove a first candidate from the first candidatelist based on the first candidate having the same reference picture listas another candidate in the first candidate list, the first candidatehaving the same reference picture list index as another candidate in thefirst candidate list, and the first candidate having a horizontal andvertical motion vector difference from another candidate in the firstcandidate list that is not greater than a threshold, and wherein toperform the second pruning process on the second candidate list, the oneor more processors are configured to: remove a second candidate from thesecond candidate list based on the second candidate having the samereference picture list as another candidate in the first candidate listor the second candidate list, the second candidate having the samereference picture list index as another candidate in the first candidatelist or the second candidate list, and the second candidate having ahorizontal and vertical motion vector difference from another candidatein the first candidate list or the second candidate list that is notgreater than the threshold.

Aspect 18C—The apparatus of any of Aspects 13C-17C, wherein the one ormore processors are further configured to: construct a final geometricpartitioning mode motion vector candidate list using the first candidatelist and the second candidate list.

Aspect 19C—The apparatus of Aspect 18C, wherein to construct the finalgeometric partitioning mode motion vector candidate list using the firstcandidate list and the second candidate list, the one or more processorsare further configured to: add the first motion vector candidates fromthe first candidate list to the final geometric partitioning mode motionvector candidate list; add, in the case that the final geometricpartitioning mode motion vector candidate list is less than apredetermined number of candidates after adding the first motion vectorcandidates, the second motion vector candidates from the secondcandidate list to the final geometric partitioning mode motion vectorcandidate list; and pad, in the case that the final geometricpartitioning mode motion vector candidate list is less than thepredetermined number of candidates after adding the first motion vectorcandidates and the second motion vector candidates, zero motion vectorcandidates to the final geometric partitioning mode motion vectorcandidate list.

Aspect 20C—The apparatus of Aspect 19C, wherein the one or moreprocessors are further configured to: perform a pruning process on thefinal geometric partitioning mode motion vector candidate list.

Aspect 21C—The apparatus of any of Aspects 19C-20C, wherein to decodethe block of video data using uni-prediction, the one or more processorsare further configured to: decode the block of video data usinguni-prediction and the final geometric partitioning mode motion vectorcandidate list.

Aspect 22C—The apparatus of any of Aspects 12C-21C, further comprising:a display configured to display a picture that includes the decodedblock of video data.

It is to be recognized that depending on the example, certain acts orevents of any of the techniques described herein can be performed in adifferent sequence, may be added, merged, or left out altogether (e.g.,not all described acts or events are necessary for the practice of thetechniques). Moreover, in certain examples, acts or events may beperformed concurrently, e.g., through multi-threaded processing,interrupt processing, or multiple processors, rather than sequentially.

In one or more examples, the functions described may be implemented inhardware, software, firmware, or any combination thereof. If implementedin software, the functions may be stored on or transmitted over as oneor more instructions or code on a computer-readable medium and executedby a hardware-based processing unit. Computer-readable media may includecomputer-readable storage media, which corresponds to a tangible mediumsuch as data storage media, or communication media including any mediumthat facilitates transfer of a computer program from one place toanother, e.g., according to a communication protocol. In this manner,computer-readable media generally may correspond to (1) tangiblecomputer-readable storage media which is non-transitory or (2) acommunication medium such as a signal or carrier wave. Data storagemedia may be any available media that can be accessed by one or morecomputers or one or more processors to retrieve instructions, codeand/or data structures for implementation of the techniques described inthis disclosure. A computer program product may include acomputer-readable medium.

By way of example, and not limitation, such computer-readable storagemedia can comprise RAM, ROM, EEPROM, CD-ROM or other optical diskstorage, magnetic disk storage, or other magnetic storage devices, flashmemory, or any other medium that can be used to store desired programcode in the form of instructions or data structures and that can beaccessed by a computer. Also, any connection is properly termed acomputer-readable medium. For example, if instructions are transmittedfrom a website, server, or other remote source using a coaxial cable,fiber optic cable, twisted pair, digital subscriber line (DSL), orwireless technologies such as infrared, radio, and microwave, then thecoaxial cable, fiber optic cable, twisted pair, DSL, or wirelesstechnologies such as infrared, radio, and microwave are included in thedefinition of medium. It should be understood, however, thatcomputer-readable storage media and data storage media do not includeconnections, carrier waves, signals, or other transitory media, but areinstead directed to non-transitory, tangible storage media. Disk anddisc, as used herein, includes compact disc (CD), laser disc, opticaldisc, digital versatile disc (DVD), floppy disk and Blu-ray disc, wheredisks usually reproduce data magnetically, while discs reproduce dataoptically with lasers. Combinations of the above should also be includedwithin the scope of computer-readable media.

Instructions may be executed by one or more processors, such as one ormore DSPs, general purpose microprocessors, ASICs, FPGAs, or otherequivalent integrated or discrete logic circuitry. Accordingly, theterms “processor” and “processing circuitry,” as used herein may referto any of the foregoing structures or any other structure suitable forimplementation of the techniques described herein. In addition, in someaspects, the functionality described herein may be provided withindedicated hardware and/or software modules configured for encoding anddecoding, or incorporated in a combined codec. Also, the techniquescould be fully implemented in one or more circuits or logic elements.

The techniques of this disclosure may be implemented in a wide varietyof devices or apparatuses, including a wireless handset, an integratedcircuit (IC) or a set of ICs (e.g., a chip set). Various components,modules, or units are described in this disclosure to emphasizefunctional aspects of devices configured to perform the disclosedtechniques, but do not necessarily require realization by differenthardware units. Rather, as described above, various units may becombined in a codec hardware unit or provided by a collection ofinteroperative hardware units, including one or more processors asdescribed above, in conjunction with suitable software and/or firmware.

Various examples have been described. These and other examples arewithin the scope of the following claims.

What is claimed is:
 1. A method of decoding video data, the methodcomprising: determining a partitioning for a block of video data usinggeometric partitioning mode; constructing two uni-prediction motionvector candidate lists for the block of video data; and decoding theblock of video data using uni-prediction based on at least one of thetwo uni-prediction motion vector candidate lists to generate a decodedblock of video data.
 2. The method of claim 1, wherein constructing twouni-prediction motion vector candidate lists for the block of video datacomprises: constructing a first candidate list of the two uni-predictionmotion vector candidate lists, including interleaving first motionvector candidates from a first reference picture list with second motionvector candidates from a second reference picture list; and constructinga second candidate list of the two uni-prediction motion vectorcandidate lists, including interleaving the second motion vectorcandidates from the second reference picture list with the first motionvector candidates from the first reference picture list.
 3. The methodof claim 2, wherein interleaving first motion vector candidates from thefirst reference picture list with second motion vector candidates fromthe second reference picture list comprises adding the first motionvector candidates and the second motion vector candidates to the firstcandidate list in an alternating fashion wherein a candidate from thefirst motion vector candidates is added first.
 4. The method of claim 2,wherein interleaving second motion vector candidates from the secondreference picture list with first motion vector candidates from thefirst reference picture list comprises adding the second motion vectorcandidates and the first motion vector candidates to the secondcandidate list in an alternating fashion wherein a candidate from thesecond motion vector candidates is added first.
 5. The method of claim2, further comprising: performing a first pruning process on the firstcandidate list; and performing a second pruning process on the secondcandidate list.
 6. The method of claim 5, wherein performing the firstpruning process on the first candidate list comprises: removing a firstcandidate from the first candidate list based on the first candidatehaving the same reference picture list as another candidate in the firstcandidate list, the first candidate having the same reference picturelist index as another candidate in the first candidate list, and thefirst candidate having a horizontal and vertical motion vectordifference from another candidate in the first candidate list that isnot greater than a threshold, and wherein performing the second pruningprocess on the second candidate list comprises: removing a secondcandidate from the second candidate list based on the second candidatehaving the same reference picture list as another candidate in the firstcandidate list or the second candidate list, the second candidate havingthe same reference picture list index as another candidate in the firstcandidate list or the second candidate list, and the second candidatehaving a horizontal and vertical motion vector difference from anothercandidate in the first candidate list or the second candidate list thatis not greater than the threshold.
 7. The method of claim 2, furthercomprising: constructing a final geometric partitioning mode motionvector candidate list using the first candidate list and the secondcandidate list.
 8. The method of claim 7, wherein constructing the finalgeometric partitioning mode motion vector candidate list using the firstcandidate list and the second candidate list comprises: adding the firstmotion vector candidates from the first candidate list to the finalgeometric partitioning mode motion vector candidate list; adding, in thecase that the final geometric partitioning mode motion vector candidatelist is less than a predetermined number of candidates after adding thefirst motion vector candidates, the second motion vector candidates fromthe second candidate list to the final geometric partitioning modemotion vector candidate list; and padding, in the case that the finalgeometric partitioning mode motion vector candidate list is less thanthe predetermined number of candidates after adding the first motionvector candidates and the second motion vector candidates, zero motionvector candidates to the final geometric partitioning mode motion vectorcandidate list.
 9. The method of claim 7, further comprising: performinga pruning process on the final geometric partitioning mode motion vectorcandidate list.
 10. The method of claim 7, wherein decoding the block ofvideo data using uni-prediction comprises: decoding the block of videodata using uni-prediction and the final geometric partitioning modemotion vector candidate list.
 11. The method of claim 1, furthercomprising: displaying a picture that includes the decoded block ofvideo data.
 12. An apparatus configured to decode video data, theapparatus comprising: a memory configured to store a block of videodata; and one or more processors in communication with the memory, theone or more processors configured to: determine a partitioning for theblock of video data using geometric partitioning mode; construct twouni-prediction motion vector candidate lists for the block of videodata; and decode the block of video data using uni-prediction based onat least one of the two uni-prediction motion vector candidate lists togenerate a decoded block of video data.
 13. The apparatus of claim 12,wherein to construct two uni-prediction motion vector candidate listsfor the block of video data, the one or more processors are furtherconfigured to: construct a first candidate list of the twouni-prediction motion vector candidate lists, including interleavingfirst motion vector candidates from a first reference picture list withsecond motion vector candidates from a second reference picture list;and construct a second candidate list of the two uni-prediction motionvector candidate lists, including interleaving the second motion vectorcandidates from the second reference picture list with the first motionvector candidates from the first reference picture list.
 14. Theapparatus of claim 13, wherein to interleave first motion vectorcandidates from the first reference picture list with second motionvector candidates from the second reference picture list, the one ormore processors are configured to add the first motion vector candidatesand the second motion vector candidates to the first candidate list inan alternating fashion wherein a candidate from the first motion vectorcandidates is added first.
 15. The apparatus of claim 13, wherein tointerleave second motion vector candidates from the second referencepicture list with first motion vector candidates from the firstreference picture list, the one or more processors are configured to addthe second motion vector candidates and the first motion vectorcandidates to the second candidate list in an alternating fashionwherein a candidate from the second motion vector candidates is addedfirst.
 16. The apparatus of claim 13, wherein the one or more processorsare further configured to: perform a first pruning process on the firstcandidate list; and perform a second pruning process on the secondcandidate list.
 17. The apparatus of claim 16, wherein to perform thefirst pruning process on the first candidate list, the one or moreprocessors are configured to: remove a first candidate from the firstcandidate list based on the first candidate having the same referencepicture list as another candidate in the first candidate list, the firstcandidate having the same reference picture list index as anothercandidate in the first candidate list, and the first candidate having ahorizontal and vertical motion vector difference from another candidatein the first candidate list that is not greater than a threshold, andwherein to perform the second pruning process on the second candidatelist, the one or more processors are configured to: remove a secondcandidate from the second candidate list based on the second candidatehaving the same reference picture list as another candidate in the firstcandidate list or the second candidate list, the second candidate havingthe same reference picture list index as another candidate in the firstcandidate list or the second candidate list, and the second candidatehaving a horizontal and vertical motion vector difference from anothercandidate in the first candidate list or the second candidate list thatis not greater than the threshold.
 18. The apparatus of claim 13,wherein the one or more processors are further configured to: constructa final geometric partitioning mode motion vector candidate list usingthe first candidate list and the second candidate list.
 19. Theapparatus of claim 18, wherein to construct the final geometricpartitioning mode motion vector candidate list using the first candidatelist and the second candidate list, the one or more processors arefurther configured to: add the first motion vector candidates from thefirst candidate list to the final geometric partitioning mode motionvector candidate list; add, in the case that the final geometricpartitioning mode motion vector candidate list is less than apredetermined number of candidates after adding the first motion vectorcandidates, the second motion vector candidates from the secondcandidate list to the final geometric partitioning mode motion vectorcandidate list; and pad, in the case that the final geometricpartitioning mode motion vector candidate list is less than thepredetermined number of candidates after adding the first motion vectorcandidates and the second motion vector candidates, zero motion vectorcandidates to the final geometric partitioning mode motion vectorcandidate list.
 20. The apparatus of claim 19, wherein the one or moreprocessors are further configured to: perform a pruning process on thefinal geometric partitioning mode motion vector candidate list.
 21. Theapparatus of claim 19, wherein to decode the block of video data usinguni-prediction, the one or more processors are further configured to:decode the block of video data using uni-prediction and the finalgeometric partitioning mode motion vector candidate list.
 22. Theapparatus of claim 12, further comprising: a display configured todisplay a picture that includes the decoded block of video data.
 23. Anon-transitory computer-readable storage medium storing instructionsthat, when executed, cause one or more processors of a device configuredto decode video data to: determine a partitioning for a block of videodata using geometric partitioning mode; construct two uni-predictionmotion vector candidate lists for the block of video data; and decodethe block of video data using uni-prediction based on at least one ofthe two uni-prediction motion vector candidate lists to generate adecoded block of video data.
 24. The non-transitory computer-readablestorage medium of claim 23, wherein to construct two uni-predictionmotion vector candidate lists for the block of video data, theinstructions further cause the one or more processors to: construct afirst candidate list of the two uni-prediction motion vector candidatelists, including interleaving first motion vector candidates from afirst reference picture list with second motion vector candidates from asecond reference picture list; and construct a second candidate list ofthe two uni-prediction motion vector candidate lists, includinginterleaving the second motion vector candidates from the secondreference picture list with the first motion vector candidates from thefirst reference picture list.
 25. The non-transitory computer-readablestorage medium of claim 24, wherein the instructions further cause theone or more processors to: perform a first pruning process on the firstcandidate list; and perform a second pruning process on the secondcandidate list.
 26. An apparatus configured to encode video data, theapparatus comprising: a memory configured to store a block of videodata; and one or more processors in communication with the memory, theone or more processors configured to: determine a partitioning for theblock of video data using geometric partitioning mode; construct twouni-prediction motion vector candidate lists for the block of videodata; and encode the block of video data using uni-prediction based onat least one of the two uni-prediction motion vector candidate lists togenerate an encoded block of video data.
 27. The apparatus of claim 26,wherein to construct two uni-prediction motion vector candidate listsfor the block of video data, the one or more processors are furtherconfigured to: construct a first candidate list of the twouni-prediction motion vector candidate lists, including interleavingfirst motion vector candidates from a first reference picture list withsecond motion vector candidates from a second reference picture list;and construct a second candidate list of the two uni-prediction motionvector candidate lists, including interleaving the second motion vectorcandidates from the second reference picture list with the first motionvector candidates from the first reference picture list.
 28. Theapparatus of claim 27, wherein the one or more processors are furtherconfigured to: perform a first pruning process on the first candidatelist; and perform a second pruning process on the second candidate list.